ABSTRACT
Chinese medicine (CM) diagnosis intellectualization is one of the hotspots in the research of CM modernization. The traditional CM intelligent diagnosis models transform the CM diagnosis issues into classification issues, however, it is difficult to solve the problems such as excessive or similar categories. With the development of natural language processing techniques, text generation technique has become increasingly mature. In this study, we aimed to establish the CM diagnosis generation model by transforming the CM diagnosis issues into text generation issues. The semantic context characteristic learning capacity was enhanced referring to Bidirectional Long Short-Term Memory (BILSTM) with Transformer as the backbone network. Meanwhile, the CM diagnosis generation model Knowledge Graph Enhanced Transformer (KGET) was established by introducing the knowledge in medical field to enhance the inferential capability. The KGET model was established based on 566 CM case texts, and was compared with the classic text generation models including Long Short-Term Memory sequence-to-sequence (LSTM-seq2seq), Bidirectional and Auto-Regression Transformer (BART), and Chinese Pre-trained Unbalanced Transformer (CPT), so as to analyze the model manifestations. Finally, the ablation experiments were performed to explore the influence of the optimized part on the KGET model. The results of Bilingual Evaluation Understudy (BLEU), Recall-Oriented Understudy for Gisting Evaluation 1 (ROUGE1), ROUGE2 and Edit distance of KGET model were 45.85, 73.93, 54.59 and 7.12, respectively in this study. Compared with LSTM-seq2seq, BART and CPT models, the KGET model was higher in BLEU, ROUGE1 and ROUGE2 by 6.00-17.09, 1.65-9.39 and 0.51-17.62, respectively, and lower in Edit distance by 0.47-3.21. The ablation experiment results revealed that introduction of BILSTM model and prior knowledge could significantly increase the model performance. Additionally, the manual assessment indicated that the CM diagnosis results of the KGET model used in this study were highly consistent with the practical diagnosis results. In conclusion, text generation technology can be effectively applied to CM diagnostic modeling. It can effectively avoid the problem of poor diagnostic performance caused by excessive and similar categories in traditional CM diagnostic classification models. CM diagnostic text generation technology has broad application prospects in the future.
Subject(s)
Humans , Medicine, Chinese Traditional , Pattern Recognition, Automated , Asian People , Language , LearningABSTRACT
To explore the methods of the explicitation of implicit knowledge and the construction of knowledge graph on moxibustion in medical case records of ZHOU Mei-sheng's Jiusheng. The medical case records data of Jiusheng was collected, the frequency statistic was analyzed based on Python3.8.6, complex network analysis was performed using Gephi9.2 software, community analysis was performed by the ancient and modern medical case cloud platform V2.3.5, and analysis and verification of correlation graph and weight graph were proceed by Neo4j3.5.25 image database. The disease systems with frequency≥10 % were surgery, ophthalmology and otorhinolaryngology, locomotor, digestive and respiratory systems. The diseases under the disease system were mainly carbuncle, arthritis, lumbar disc herniation and headache. The commonly used moxibustion methods were fumigating moxibustion, blowing moxibustion, direct moxibustion and warming acupuncture. The core prescription of points obtained by complex network analysis included Yatong point, Zhiyang(GV 9), Sanyinjiao(SP 6), Dazhui(GV 14), Zusanli(ST 36), Lingtai(GV 10), Xinshu(BL 15), Zhijian point and Hegu(LI 4), which were basically consistent with high-frequency points. A total of 6 communities were obtained by community analysis, corresponding to different diseases. Through the analysis of correlation graph, 13 pairs of strong association rule points were obtained. The correlation between Zhiyang(GV 9)-Dazhui(GV 14) and Yatong point-Lingtai(GV 10) was the strongest. The acupoints with high correlation with Yatong point were Zhiyang(GV 9), Lingtai(GV 10), Dazhui(GV 14), Zusanli(ST 36) and Sanyinjiao(SP 6). In the weight graph of the high-frequency disease system, the relationship of the first weight of the surgery system disease was fumigating moxibustion-carbuncle-Yatong point, and the relationship of the first weight of the ophthalmology and otorhinolaryngology system disease was blowing moxibustion-laryngitis-Hegu (LI 4). The results of correlation graph and weight graph are consistent with the results of data mining, which can be used as an effective way to study the knowledge base of moxibustion diagnosis and treatment in the future.
Subject(s)
Humans , Moxibustion , Carbuncle , Pattern Recognition, Automated , Acupuncture Therapy , Acupuncture PointsABSTRACT
Bibliometric and scientific knowledge graph methods were used to analyze the research status and hot spots of acupuncture-moxibustion in treatment of myofascial pain syndrome (MPS) and explore its development trend. The articles of both Chinese and English versions relevant to MPS treated by acupuncture-moxibustion were searched in CNKI, VIP, Wanfang, SinoMed and WOS from the database inception to March 20, 2023. Using Excel2016, CiteSpace6.2.R2 and VOSviewer1.6.18, the visual analysis was conducted by means of the cooperative network, keyword co-occurrence, keyword timeline, keyword emergence, etc. From Chinese databases and WOS database, 910 Chinese articles and 300 English articles were included, respectively. The annual publication volume showed an overall rising trend. Literature output of English articles was concentrated in Spain, China, and the United States, of which, there was less cross-regional cooperation. In the keyword analysis, regarding acupuncture-moxibustion therapy, Chinese articles focused on "acupuncture", "electroacupuncture" and "acupotomy"; while, "dry needling" and "injection" were dominated for English one. Clinical study was the current hot spot in Chinese databases, in comparison, the randomized controlled double-blind clinical trial was predominant in WOS. Both Chinese and English articles were limited in the report of mechanism research. The cooperation among research teams should be strengthened to conduct comparative research, dose-effect research and effect mechanism research with different methods of acupuncture-moxibustion involved so that the evidences can be provided for deeper exploration.
Subject(s)
Humans , Moxibustion , Pattern Recognition, Automated , Acupuncture Therapy , Myofascial Pain Syndromes/therapy , ElectroacupunctureABSTRACT
With the booming development of medical information technology and computer science, the medical services industry is gradually transiting from information technology to intelligence. The medical knowledge graph plays an important role in intelligent medical applications such as knowledge questions and answers and intelligent diagnosis, and is a key technology for promoting wise medical care and the basis for intelligent management of medical information. In order to fully exploit the great potential of knowledge graphs in the medical field, this paper focuses on five aspects: inter-drug relationship discovery, assisted diagnosis, personalized recommendation, decision support and intelligent prediction. The latest research progress on medical knowledge graphs is introduced, and relevant suggestions are made in light of the current challenges and problems faced by medical knowledge graphs to provide reference for promoting the wide application of medical knowledge graphs.
Subject(s)
Pattern Recognition, Automated , Medical InformaticsABSTRACT
To explore the research hotspots and frontier directions of pyroptosis in the field of traditional Chinese medicine(TCM), the authors searched CNKI and Web of Science for literature related to pyroptosis in TCM, screened literature according to the search strategy and inclusion criteria, and analyzed the publication trend of the included literature. VOSviewer was used to draw author cooperation and keyword co-occurrence network diagrams, and CiteSpace was employed for keyword clustering, emergence, and timeline view. Finally, 507 Chinese literature and 464 English literature were included, and it was found that the number of Chinese and English literature was increasing rapidly year by year. The co-occurrence of the authors showed that in terms of Chinese literature, there was a representative research team composed of DU Guan-hua, WANG Shou-bao and FANG Lian-hua, and for English literature, the representative research team was composed of XIAO Xiao-he, BAI Zhao-fang and XU Guang. The network visualization of Chinese and English keywords revealed that inflammation, apoptosis, oxidative stress, autophagy, organ damage, fibrosis, atherosclerosis, and ischemia-reperfusion injury were the primary research diseases and pathological processes in TCM; berberine, resveratrol, puerarin, na-ringenin, astragaloside Ⅳ, and baicalin were the representative active ingredients; NLRP3/caspase-1/GSDMD, TLR4/NF-κB/NLRP3, and p38/MAPK signaling pathways were the main research pathways. Keyword clustering, emergence, and timeline analysis indicated that the pyroptosis research in TCM focused on the mechanism of TCM monomers and compounds intervening in diseases and pathological processes. Pyroptosis is a research hotspot in the area of TCM, and the current discussion mainly focuses on the mechanism of the therapeutic effect of TCM.
Subject(s)
Pyroptosis , Medicine, Chinese Traditional , NLR Family, Pyrin Domain-Containing 3 Protein , Pattern Recognition, Automated , ApoptosisABSTRACT
Introducción: La actividad física insuficiente es uno de los principales problemas de salud pública a nivel global. Los patrones de conducta en los adolescentes, y el estilo de vida, podrían afectar su salud física y mental. Objetivos: El objetivo de este estudio fue conocer los patrones de actividad física y los comportamientos sedentarios en la población de adolescentes a nivel nacional. Materiales y métodos: Estudio cuantitativo, observacional, descriptivo de corte transverso, se aplicó el cuestionario de la Encuesta Global de Salud Escolar en adolescentes escolares del octavo y noveno grados del 3° ciclo de la Educación Escolar Básica y al 1°, 2° y 3° cursos de la Educación Media de 49 escuelas y colegios del país. En este estudio fueron incluidos 1.803 estudiantes de edades comprendidas entre 13 a 15 años. Resultados: El 27% de los adolescentes de 13 a 15 años de Paraguay son activos, siendo significativamente mayor en hombres que en mujeres (p-valor 0,000) y el 22% son inactivos con mayor frecuencia en mujeres que en hombres (p-valor 0,000). Se observo que el 33,5% de los adolescentes tenían comportamiento sedentario, el 43,4% de los adolescentes no utilizo el desplazamiento activo para asistir a la escuela. Los adolescentes que no participaron de las clases de educación física en la escuela representaron el15,6%. Conclusión: Si bien en un 27% los adolescentes de 13 a 15 años son activos, es preocupante el gran porcentaje de adolescentes inactivos y con comportamiento sedentario.
Introduction: Insufficient physical activity is one of the main public health problems globally. Teen behavior patterns and lifestyle may affect their physical and mental health. Objectives: The objective of this study was to know the patterns of physical activity and sedentary behaviors in the adolescent population nationwide. Materials and methods: A quantitative, observational, descriptive cross-sectional study, the questionnaire of the Global School Health Survey was applied in school adolescents of the eighth and ninth grades of the 3rd cycle of Basic School Education and the 1st, 2nd and 3rd year of Secondary Education in 49 schools and colleges in the country. 1,803 students aged 13 to 15 years were included in this study. Results: 27% of adolescents between the ages of 13 and 15 in Paraguay are active, being significantly higher in men than in women (p-value 0.000) and 22% are inactive more frequently in women than in men (p-value 0.000). It was observed that 33.5% of the adolescents had sedentary behavior, 43.4% of the adolescents did not use active displacement to attend school. Adolescents who did not participate in physical education classes at school accounted for 15.6%. Conclusion: Although 27% of adolescents between the ages of 13 and 15 are active, the large percentage of inactive adolescents with sedentary behavior is worrying.
Subject(s)
Exercise , Sedentary Behavior , Pattern Recognition, Automated/classification , Exercise/physiology , Adolescent/physiologyABSTRACT
SUMMARY: The aim of this exploratory design science research (DSR) study was to design a computer-based teaching simulation tool (CBTST) for training medical imaging (MI) students in chest pattern recognition. A DSR methodology used in the design of the CBTST entailed the following phases: 1) awareness of the problem (proposal design); 2) suggestion; 3) development; 4) evaluation; and 5) conclusion. The CBTST was designed using Microsoft Visual Studio which operates on the Structured Query Language server. The designed CBTST was evaluated using the System Usability Scale (SUS) and MI educators. The designed CBTST evaluation yielded an average score of 70.1 which exceeded the score of 68 which is generally accepted to indicate that the CBTST has good usability. The CBTST proved to be an authentic tool that is user-friendly and allows communication and feedback between the educator and the students. It is envisaged that the implementation of this tool will enhance the future training of MI students in pattern recognition while contributing immensely to the current development of the use of computer-based simulation.
RESUMEN: El objetivo de este estudio de investigación en ciencias de diseño (DSR) fue desarrollar una herramienta de simulación de enseñanza basada en computadora (CBTST) para capacitar a los estudiantes en el reconocimiento de patrones de tórax a través de la imagenología médica. Una metodología DSR utilizada en el diseño del CBTST implicaba las siguientes fases: 1) conciencia del problema (diseño de la propuesta); 2) sugerencia; 3) desarrollo; 4) evaluación; y 5) conclusión. El CBTST se diseñó con Microsoft Visual Studio, que opera en el servidor de Structured Query Language. El CBTST diseñado se evaluó utilizando la escala de usabilidad del sistema (SUS) y educadores de IM. La evaluación CBTST diseñada arrojó un puntaje promedio de 70,1 que excedió el puntaje de 68 que generalmente se acepta para indicar que el CBTST tiene buena usabilidad. El CBTST demostró ser una herramienta auténtica, fácil de usar y que permite la comunicación y la retroalimentación entre el educador y los estudiantes. Se prevé que la implementación de esta herramienta mejorará la formación futura de los estudiantes de IM en el reconocimiento de patrones y contribuirá de manera importante al desarrollo actual del uso de la simulación basada en computadora.
Subject(s)
Humans , Thorax/diagnostic imaging , Computer Simulation , Pattern Recognition, Automated , Computer-Assisted Instruction/methods , Education, Medical/methods , Aptitude , Software , Education, Medical, Undergraduate , Educational Measurement , Simulation Training/methods , Anatomy/educationABSTRACT
According to the requirements for developing the quality control technology in Chinese medicine( CM) manufacturing process and the practical scenarios in applying a new generation of artificial intelligence to CM industry,we present a method of constructing the knowledge graph( KG) for CM manufacture to solve key problems about quality control in CM manufacturing process.Based on the above,a " pharmaceutical industry brain" model for CM manufacture has been established. Further,we propose founding the KG-based methodology for quality control in CM manufacturing process,and briefly describe the design method,system architecture and main functions of the KG system. In this work,the KG for manufacturing Shuxuening Injection( SXNI) was developed as a demonstration study. The KG version 1. 0 platform for intelligent manufacturing SXNI has been built,which could realize technology leap of the quality control system in CM manufacturing process from perceptual intelligence to cognitive intelligence.
Subject(s)
Artificial Intelligence , Drug Industry/standards , Drugs, Chinese Herbal/standards , Medicine, Chinese Traditional/standards , Pattern Recognition, Automated , Quality Control , Technology, PharmaceuticalABSTRACT
Brain-computer interface (BCI) provides a direct communicating and controlling approach between the brain and surrounding environment, which attracts a wide range of interest in the fields of brain science and artificial intelligence. It is a core to decode the electroencephalogram (EEG) feature in the BCI system. The decoding efficiency highly depends on the feature extraction and feature classification algorithms. In this paper, we first introduce the commonly-used EEG features in the BCI system. Then we introduce the basic classical algorithms and their advanced versions used in the BCI system. Finally, we present some new BCI algorithms proposed in recent years. We hope this paper can spark fresh thinking for the research and development of high-performance BCI system.
Subject(s)
Humans , Algorithms , Brain , Physiology , Brain-Computer Interfaces , Electroencephalography , Pattern Recognition, AutomatedABSTRACT
Resumen Se presentan los resultados de una investigación, cuyo objetivo es identificar patrones de conocimiento significativo en el contenido de la documentación presentada para la evaluación del Ambiente Organizacional de 13 empresas mexicanas, que integran el ranking de Súper Empresas ® elaborado por la Consultora Top Companies ® . Por medio del procesamiento cuantitativo de seis variables, seis indicadores y el Análisis de Redes Sociales, se visualizan mapas de relaciones entre las empresas y los atributos de las variables seleccionadas. Con el uso de la fuente y la metodología empleadas se revelan patrones de comportamiento informativo presentes en la documentación objeto de estudio que aportan nuevo conocimiento para la toma de decisiones sobre la evaluación y la elaboración de los rankings empresariales que generan las consultoras especializadas sobre la referida temática.
Abstract This paper reports the results of research aimed at identifying patterns of significant knowledge contained in the documentation of thirteen Mexican companies submitted for the purpose of the Organizational Environment evaluation of "Super Companies", a ranking issued exclusively by the consulting firm Top Companies®. Maps of company relationships and the attributes of the selected variables are developed on the basis of the quantitative processing of six variables and indicators, and an analysis of social networks. The sources and the methodology employed reveal patterns of informational behavior in the specialized documentation that can serve to support decision making with regard to the evaluation and preparation of the rankings issued by the specialized consultants.
Subject(s)
Pattern Recognition, Automated , Organizations/trends , Capacity Building , Information Management/statistics & numerical data , Internet Access , Social Network Analysis , Data Analysis , MexicoABSTRACT
OBJECTIVES: Clinical discharge summaries provide valuable information about patients' clinical history, which is helpful for the realization of intelligent healthcare applications. The documents tend to take the form of separate segments based on temporal or topical information. If a patient's clinical history can be seen as a consecutive sequence of clinical events, then each temporal segment can be seen as a snapshot, providing a certain clinical context at a specific moment. This study aimed to demonstrate a temporal segmentation method of Korean clinical narratives for identifying textual snapshots of patient history as a proof-of-a-concept. METHODS: Our method uses pattern-based segmentation to approximate human recognition of the temporal or topical shifts in clinical documents. We utilized rheumatic patients' discharge summaries and transformed them into sequences of constituent chunks. We built 97 single pattern functions to denote whether a certain chunk has attributes that indicate that it can be a segment boundary. We manually defined the relationships between the pattern functions to resolve multiple pattern matchings and to make a final decision. RESULTS: The algorithm segmented 30 discharge summaries and processed 1,849 decision points. Three human judges were asked whether they agreed with the algorithm's prediction, and the agreement percentage on the judges' majority opinion was 89.61%. CONCLUSIONS: Although this method is based on manually constructed rules, our findings demonstrate that the proposed algorithm can achieve fairly good segmentation results, and it may be the basis for methodological improvement in the future.
Subject(s)
Humans , Delivery of Health Care , Electronic Health Records , Methods , Natural Language Processing , Pattern Recognition, Automated , Rheumatic DiseasesABSTRACT
Resumen Introducción: La Organización Panamericana de la Salud (OPS) desde el año 1993 y la Organización Mundial de la Salud (OMS) en 1996, aceptaron que la violencia es un problema de salud pública, situación que se corrobora en el Informe de Violencia y Salud, en el cual América Latina presentó una tasa de homicidios de 18 por cada 100.000 personas, y es considerada como una de las regiones más violentas del mundo. Objetivo: Detectar patrones delictivos con técnicas de minería de datos en el Observatorio del Delito del municipio de Pasto (Colombia). Materiales y métodos: Se aplicó Cross Industry Standard Process for Data Mining (CRISP-DM), una de las metodologías utilizadas en el desarrollo de proyectos de minería de datos en los ambientes académico e industrial. La fuente de información fue el Observatorio del Delito del municipio de Pasto, donde está almacenadas las cifras históricas, limpias y transformadas sobre las lesiones de causa externa (fatales y no fatales), registrados en 11 años. Resultados: Se construyó un modelo de clasificación basado en árboles de decisión que permitió descubrir patrones de muertes por causa externa. Para el caso de homicidios, estos sucedieron en su mayoría en la Comuna 5 de Pasto, los fines de semana, en la madrugada, en el segundo semestre del año, en la vía pública y las víctimas fueron hombres adultos, de oficios varios, la causa de los homicidios fueron riñas y se produjeron con arma de fuego. Conclusión: El conocimiento generado ayudará a los organismos gubernamentales y de seguridad a tomar decisiones eficaces en lo relacionado a la implementación de planes de prevención de delitos y seguridad ciudadana.
Abstract Introduction: The Pan American Health Organization (PHO) and the World Health Organization (WHO) accepted, since the year 1993 and 1996 respectively, that violence is a public health problem, a situation that is corroborated in the report on violence and health, in which Latin America presented a homicide rate of 18 per 100,000 people, and it is considered one of the most violent regions in the world. Objective: To detect criminal patterns with data mining techniques in the Crime Observatory of the municipality of Pasto (Colombia). Materials and methods: Cross Industry Standard Process for Data Mining (CRISP-DM) was applied, which is one of the methodologies used in the development of data mining projects in academic and industrial environments. The source of information was the Crime Observatory of the municipality of Pasto, where the historical clean and transformed figures on the injuries of external cause (fatal and nonfatal) recorded in 11 years are stored. Results: A decision tree-based classification model was built that allowed the discovery of patterns of deaths from external causes. In the case of homicide, these happened mostly in the commune 5 in Pasto under the following circumstances: during the weekends, in the early morning, in the second semester of the year and in the public thoroughfare; besides, the victims were adult men of various professions; and the cause of the homicides were quarrels and they were produced with a fire gun. Conclusion: The generated knowledge will help government and security agencies make effective decisions regarding the implementation of crime prevention and citizen security plans.
Subject(s)
Pattern Recognition, Automated , Classification , Data Mining , Decision TreesABSTRACT
Background: A method to track liver tumor motion signals from fluoroscopic images without any implanted gold fiducial markers was proposed in this study to overcome the adverse effects on precise tumor irradiation caused by respiratory movement
Materials and Methods: The method was based on the following idea: [i] Before treatment, a series of fluoroscopic images corresponding to different breathing phases and tumor positions were acquired after patient set-up; [iii] The wavelet transform method and Canny edge detection algorithm were used to detect motion trajectory of the diaphragm; [iv] The motion curves of center of lipiodol in the images were obtained by mathematical morphology and median filtering algorithm. The method was evaluated using by five sequences of fluoroscopic images from TACE patients who received transcatheter arterial chemoembolization therapy
Results: The position of liver tumor was significantly affected by respiratory motion; the motion trajectories of the diaphragm and lipiodolagreed well with the manually marked locations in amplitude and period; the motion trajectories of the diaphragm and lipiodol almost had similar period and amplitude in one treatment fraction. The respiratory period and amplitude of the same patient in different fractions had no significant differences; however, the difference was obvious for different patients. The proposed lipiodol detection methods can effectively reflect the relevant rules of tumor location caused by respiratory movement
Conclusion: Direct tracking of liver tumor motion in fluoroscopic images is feasible. The automatic detection method can reflect the characteristics of respiratory and tumor motions, which can save much time and significantly improve measurement precision compared with manual measurement
Subject(s)
Humans , Male , Middle Aged , Chemoembolization, Therapeutic , Fiducial Markers , Radiotherapy, Image-Guided , Fluoroscopy , Pattern Recognition, Automated/methodsABSTRACT
OBJECTIVE: To assess the maturation disparity of hand-wrist bones using the BoneXpert system and Greulich and Pyle (GP) atlas in a sample of normal children from China. MATERIALS AND METHODS: Our study included 229 boys and 168 girls aged 2-14 years. The bones in the hand and wrist were divided into five groups: distal radius and ulna, metacarpals, proximal phalanges, middle phalanges and distal phalanges. Bone age (BA) was assessed separately using the automatic BoneXpert and GP atlas by two raters. Differences in the BA between the most advanced and retarded individual bones and bone groups were analyzed. RESULTS: In 75.8% of children assessed with the BoneXpert and 59.4% of children assessed with the GP atlas, the BA difference between the most advanced and most retarded individual bones exceeded 2.0 years. The BA mean differences between the most advanced and most retarded individual bones were 2.58 and 2.25 years for the BoneXpert and GP atlas methods, respectively. Furthermore, for both methods, the middle phalanges were the most advanced group. The most retarded group was metacarpals for BoneXpert, while metacarpals and the distal radius and ulna were the most retarded groups according to the GP atlas. Overall, the BAs of the proximal and distal phalanges were closer to the chronological ages than those of the other bone groups. CONCLUSION: Obvious and regular maturation disparities are common in normal children. Overall, the BAs of the proximal and distal phalanges are more useful for BA estimation than those of the other bone groups.
Subject(s)
Child , Female , Humans , Age Determination by Skeleton , Asian People , Bone and Bones , China , Developmental Disabilities , Hand , Metacarpal Bones , Pattern Recognition, Automated , Radiography , Radius , Ulna , WristABSTRACT
<p><b>OBJECTIVE</b>To review theories and technologies of big data mining and their application in clinical medicine.</p><p><b>DATA SOURCES</b>Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015.</p><p><b>STUDY SELECTION</b>Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected.</p><p><b>RESULTS</b>This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine.</p><p><b>CONCLUSION</b>Big data mining has the potential to play an important role in clinical medicine.</p>
Subject(s)
Humans , Bayes Theorem , Clinical Medicine , Data Mining , Decision Support Systems, Clinical , Decision Trees , Evidence-Based Medicine , Fuzzy Logic , Neural Networks, Computer , Pattern Recognition, AutomatedABSTRACT
Este estudo analisou a eficiência de diferentes algoritmos de máquina de vetor de suporte (SVM) para discriminar dados de diferentes sujeitos. Utilizou-se dados previamente coletados de idosos e jovens com 3 coletas por sujeito, em um estudo de controle postural na plataforma de força. Os dados foram analisados a partir da densidade espectral de potência (PSD) do centro de pressão sobre a qual foi aplicada a análise de componentes principais (PCA) para reduzir a dimensionalidade dos dados. A SVM recebeu a PCA com 90% de variância da PSD original e utilizando diferentes núcleos de produto interno calculou a eficiência de cada um para diferenciar grupos com características distintas.A SVM que obteve o melhor desempenho foi a de núcleo Polinomial, com uma eficiência de 90% aproximadamente, no entanto, o resultado é dependente dos dados a serem classificados, e se faz necessário então uma ferramenta que possa utilizar diferentes núcleos.
This study analyze the efficiency of different algorithms of support vector machine (SVM) to discriminate data from different subjects. It was used data previously collected from elderly and young people with 3 collectionsby subject, in a postural control study on a force plate. Data were analyzed from the power spectral density (PSD)of the center of pressure on which was applied principal component analysis (PCA) to reduce the dimensionality ofthe data. The SVM received the PCA with 90% of the variance of the original PSD and using different inner productkernels was calculated the efficiency of each one to differentiate between groups with different characteristics. TheSVM that have the best performances was the Polynomial with an efficiency of 90% approximately, however, the result depends on data to be classified and it is necessary then a tool that can use different cores.
Subject(s)
Humans , Signal Processing, Computer-Assisted , Pattern Recognition, Automated , Neural Networks, Computer , Congresses as TopicABSTRACT
O presente trabalho teve por objetivo demonstrar a melhora no desempenho da classificação de coloração imuno-histoquímica em imagens microscópicas, utilizando a abordagem de aprendizado supervisionada que emprega a projeção polinomial da distância de Mahalanobis. Foi definido um descritor de características híbrido, combinando core textura baseada no método Local Binary Pattern, proporcionado inicialmente um descritor 23-dimensional para cada píxel. Uma análise de componentes principais foi realizada e um segundo descritor 12-dimensional foi empregado na avaliação. Os testes foram realizados em imagens e metadados obtidos no The Human Protein Atlas, avaliando uma série de medidas de acerto e erro. Com os resultados encontrados percebeu-se que a utilização do descritor híbrido tornou o processo de classificação mais específico e restritivo nas predições positivas.
This study aimed to demonstrate the improvement in performance of immunohistochemical staining classification in microscopic images using a supervised learning approach that employs the polynomial projection of the Mahalanobis distance. A hybrid feature descriptor was defined by combining color and texture based on Local Binary Pattern method, initially provided a 23-dimensional descriptor, for each pixel. A principal component analysis was performed and a second 12-dimensional descriptor was used in the assay. The tests were performed on images and metadata, obtained on The Human Protein Atlas. With the results it can be seen that the use of hybrid descriptor has made the classification process more specific and restrictive on the positive predictions.
Subject(s)
Humans , Image Processing, Computer-Assisted , Pattern Recognition, Automated , Immunohistochemistry/classification , Congresses as TopicABSTRACT
BACKGROUND AND OBJECTIVES: Intraoperative use of opioids may be associated with postoperative hyperalgesia and increased analgesic consumption. Side effects due to perioperative use of opioids, such as postoperative nausea and vomiting may delay discharge. We hypothesized that total intravenous anesthesia consisting of lidocaine and dexmedetomidine as an opioid substitute may be an alternative technique for laparoscopic cholecystectomy and would be associated with lower fentanyl requirements in the postoperative period and less incidence of postoperative nausea and vomiting. METHODS: 80 Anesthesiologists I-II adults were scheduled for elective laparoscopic cholecystectomy. Patients were randomly allocated into two groups to have either opioid-free anesthesia with dexmedetomidine, lidocaine, and propofol infusions (Group DL) or opioid-based anesthesia with remifentanil, and propofol infusions (Group RF). All patients received a standard multimodal analgesia regimen. A patient controlled analgesia device was set to deliver IV fentanyl for 6 h after surgery. The primary outcome variable was postoperative fentanyl consumption. RESULTS: Fentanyl consumption at postoperative 2nd hour was statistically significantly less in Group DL, compared with Group RF, which were 75 ± 59 µg and 120 ± 94 µg respectively, while it was comparable at postoperative 6th hour. During anesthesia, there were more hypotensive events in Group RF, while there were more hypertensive events in Group DL, which were both statistically significant. Despite higher recovery times, Group DL had significantly lower pain scores, rescue analgesic and ondansetron need. CONCLUSION: Opioid-free anesthesia with dexmedetomidine, lidocaine and propofol infusions may be an alternative technique for laparoscopic cholecystectomy especially in patients with high risk for postoperative nausea and vomiting. .
JUSTIFICATIVA E OBJETIVOS: O uso de opioides no período intraoperatório pode estar associado à hiperalgesia e ao aumento do consumo de analgésicos no período pós-operatório. Efeitos colaterais como náusea e vômito no período pós-operatório, por causa do uso perioperatório de opioides, podem prolongar a alta. Nossa hipótese foi que a anestesia venosa total com o uso de lidocaína e dexmedetomidina em substituição a opioides pode ser uma técnica opcional para a colecistectomia laparoscópica e estaria associada a uma menor solicitação de fentanil e incidência de náusea e vômito no período pós-operatório. MÉTODOS: Foram programados para colecistectomia laparoscópica eletiva 80 pacientes adultos, estado físico ASA I-II. Os pacientes foram randomicamente alocados em dois grupos para receber anestesia livre de opioides com infusões intravenosas (IV) de dexmedetomidina, lidocaína e propofol (Grupo DL) ou anestesia baseada em opioides com infusões de remifentanil e propofol (Grupo RF). Todos os pacientes receberam um regime padrão de analgesia multimodal. Um dispositivo de analgesia controlada pelo paciente foi ajustado para liberar fentanil IV por seis horas após a cirurgia. O desfecho primário foi o consumo de fentanil no pós-operatório. RESULTADOS: O consumo de fentanil na segunda hora de pós-operatório foi significativamente menor no grupo DL do que no Grupo RF, 75 ± 59 µg e 120 ± 94 µg, respectivamente, mas foi comparável na sexta hora de pós-operatório. Durante a anestesia, houve mais eventos hipotensivos no Grupo RF e mais eventos hipertensivos no grupo DL, ambos estatisticamente significativos. Apesar de apresentar um tempo de recuperação mais prolongado, o Grupo DL apresentou escores de dor e consumo de analgésicos de resgate e de ondansetrona significativamente mais baixos. CONCLUSÃO: A anestesia livre de opioides com infusões de dexmedetomidina, lidocaína e propofol pode ser uma técnica opcional para a colecistectomia laparoscópica, ...
JUSTIFICACIÓN Y OBJETIVOS: El uso de opiáceos en el período intraoperatorio puede estar asociado con la hiperalgesia y con el aumento del consumo de analgésicos en el período postoperatorio. Los efectos colaterales como náuseas y vómito en el período postoperatorio, debido al uso perioperatorio de opiáceos, pueden retrasar el alta. Nuestra hipótesis fue que la anestesia venosa total con el uso de lidocaína y dexmedetomidina como reemplazo de los opiáceos puede ser una técnica alternativa para la colecistectomía laparoscópica y estaría asociada con un requerimiento menor de fentanilo y con una menor incidencia de náuseas y vómito en el período postoperatorio. MÉTODOS: Ochenta pacientes adultos, estado físico ASA I-II, fueron programados para colecistectomía laparoscópica electiva. Los pacientes fueron divididos aleatoriamente en 2 grupos para recibir anestesia libre de opiáceos con infusiones de dexmedetomidina, lidocaína y propofol (grupo DL), o anestesia basada en opiáceos con infusiones de remifentanilo y propofol (grupo RF). Todos los pacientes recibieron un régimen estándar de analgesia multimodal. Un dispositivo de analgesia controlada por el paciente fue ajustado para liberar el fentanilo intravenoso durante 6 h después de la cirugía. El resultado primario fue el consumo de fentanilo en el postoperatorio. RESULTADOS: El consumo de fentanilo en la segunda hora del postoperatorio fue significativamente menor en el grupo DL que en el grupo RF, 75 ± 59 µg y 120 ± 94 µg, respectivamente, pero se pudo comparar en la sexta hora del postoperatorio. Durante la anestesia hubo más eventos hipotensivos en el grupo RF y más eventos hipertensivos en el grupo DL, ambos estadísticamente significativos. A pesar de presentar un tiempo de recuperación más prolongado, el grupo DL tuvo puntuaciones de dolor y consumo de analgésicos de rescate y de ondansetrón significativamente más bajos. CONCLUSIÓN: La anestesia libre de opiáceos con infusiones de ...
Subject(s)
Animals , Female , Mice , Embryo, Mammalian/physiology , Image Interpretation, Computer-Assisted , X-Ray Microtomography/methods , Algorithms , Alleles , Automation , Databases, Factual , Image Processing, Computer-Assisted , Imaging, Three-Dimensional , Mice, Knockout , Mice, Mutant Strains , Pattern Recognition, Automated , Phenotype , SoftwareABSTRACT
RESUMOObjetivo:caracterizar as famílias e situação de saúde de idosos na Estratégia de Saúde da Família e verificar a associação da composição familiar com as características sociodemográficas e de saúde dos idosos.Método:estudo de base populacional, com 215 famílias e 266 idosos, adscritos à Estratégia da Saúde da Família, de um município do Rio Grande do Sul.Resultados:predomínio da composição familiar nuclear, considerada como a principal fonte de apoio informal, de famílias de idosos do sexo feminino e agravos cardiovasculares. A estrutura parental nuclear teve associação bruta significativa com o sexo feminino e o consumo do tabaco.Conclusão:os resultados reforçam a necessidade de manutenção de uma rede de apoio formal e informal ao idoso e sua família para preservar a independência ou postergar o declínio da capacidade funcional.
RESUMENObjetivo:la caracterización de las familias y de la situación de salud de ancianos en la Estrategia de Salud de la Familia y, además, la verifi cación de la asociación de la composición familiar con las características sociodemográfi cas y de salud de los mayores.Método:estudio de base poblacional, con 215 familias y 266 ancianos, adscritos a la Estrategia de Salud de la Familia, de un municipio del Rio Grande del Sur. Prevaleció la composición familiar nuclear, considerada como la principal fuente de apoyo informal y de familias de ancianos del sexo femenino (62,6%).Resultados:los resultados de la asociación bruta de las variables en el estudio con la composición parental nuclear ha demostrado asociación signifi cativa (p<0,05) con el sexo femenino (RP=0,77; p=0,025) y el consumo de tabaco (RP=1,35; p=0,009).Conclusión:estos resultados refuerzan la necesidad de manutención de una red de apoyo formal e informal al anciano y a su familia para preservar la independencia o postergar el descenso de la capacidad funcional.
ABSTRACTObjective:to characterize families and health status of the elderly in the Family Health Strategy and to verify the association of family composition with sociodemographic characteristics and health of the elderly.Method:population-based study with 215 families and 266 elderly, linked to the Family Health Strategy from a city of Rio Grande do Sul state.Results:there was predominance of nuclear family composition, considered as the main source of informal support, families of female elderly (62.6%) and cardiovascular complication. The nuclear structure was signifi cantly associated with female gender (PR = 0.77; p = 0.025) and smoking (PR = 1.35; p = 0.009).Conclusion:the results reinforce the need to maintain a network of formal and informal support to the elderly and their families to preserve the independence or to postpone the decline in functional capacity.
Subject(s)
Humans , Female , Aged , Breast Neoplasms , Mammography , Pattern Recognition, Automated , Radiographic Image Interpretation, Computer-Assisted , Breast Neoplasms/pathology , Clinical Competence , Mammography/methods , Mass Screening/methods , Observer Variation , Program Evaluation , Prospective Studies , Radiology/standards , Reproducibility of ResultsABSTRACT
Para estimar el costo económico de la discapacidad permanente causada por lesiones de tránsito en México durante 2012, desde las perspectivas del Sistema de Salud y de la Sociedad, se realizó un estudio de costos que utiliza metodología bottom-up, considerando costos directos médicos (hospitalización, consultas ambulatorias y de rehabilitación y prótesis), y costos indirectos (pérdida de productividad del lesionado y cuidador) con una aproximación de capital humano. La discapacidad causada por lesiones de tránsito tiene un alto costo para el sistema de salud y la sociedad mexicana. Desde la perspectiva del sistema de salud, el costo en pesos mexicanos de la discapacidad permanente fue de US$269.529.480,72, equivalente a US$1.496,33 por persona. Desde la perspectiva de la sociedad, se estimaron US$3.445,45 durante el primer año. En promedio, se estimó un costo total de US$4.941,77 por persona, resultando en un total de US$1.119.761.632,53 en 2012. Los resultados de este estudio evidencian la necesidad de diseñar e implementar políticas más enérgicas y eficientes para el control de las lesiones de tránsito en México.
This study estimated the economic costs of permanent disability caused by road traffic injuries in Mexico during 2012. From the health system's perspective, a bottom-up approach was used to calculate direct medical costs (hospitalization, outpatient care, rehabilitation, and prostheses). From society's perspective, using a human capital approach, indirect costs were associated with loss of productivity for the victims and their caregivers. Permanent disability due to road traffic injuries takes a high toll on the health system and Mexican society. From the health system perspective, the cost was US$269,529,480.72, or US$1,496.33 per victim. The estimated average cost to society was US$3,445.45 during the first year. The total average cost per victim was US$4,941.77, resulting in a total economic cost of US$1,119,761,632.53 during 2012. The study's findings highlight the need to design and implement more rigorous and efficient public polices to control and prevent road traffic injuries in Mexico.
Para estimar o custo econômico da incapacidade permanente causada por acidentes de trânsito no México no ano de 2012, com base nas perspectivas do Sistema de Saúde e da sociedade, foi realizado um estudo de custos utilizando-se a metodologia bottom-up, considerando por um lado os custos diretos médicos (hospitalização, consultas ambulatoriais e de reabilitação e próteses) e, por outro, os custos indiretos associados à perda de produtividade do acidentado e cuidador, usando-se a aproximação metodológica do capital humano. A incapacidade causada por acidentes de trânsito tem um alto custo para o sistema de saúde e sociedade mexicana. Baseando-se na perspectiva do sistema de saúde, o custo em pesos mexicanos da incapacidade permanente foi de US$269.529.480,72, equivalente a US$1.496,33 por pessoa. Com base na perspectiva da sociedade, estimou-se em US$3.445,45 no primeiro ano. Em média, estimou-se um custo total de US$4.941,77 por pessoa, resultando num total de US$1.119.761.632,53 em 2012. Os resultados deste estudo evidenciam a necessidade de delinear e implementar políticas mais rígidas no México.