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Introducción. La diabetes es una enfermedad crónica que se caracteriza por el aumento de la concentración de la glucosa en sangre. Puede generar complicaciones que afectan la calidad de vida y aumentan los costos de la atención en salud. En los últimos años, las tasas de prevalencia y mortalidad han aumentado en todo el mundo. El desarrollo de modelos con gran desempeño predictivo puede ayudar en la identificación temprana de la enfermedad. Objetivo. Desarrollar un modelo basado en la inteligencia artificial para apoyar la toma de decisiones clínicas en la detección temprana de la diabetes. Materiales y métodos. Se llevó a cabo un estudio de corte transversal, utilizando un conjunto de datos que incluía edad, signos y síntomas de pacientes con diabetes y de individuos sanos. Se utilizaron técnicas de preprocesamiento para los datos. Posteriormente, se construyó el modelo basado en mapas cognitivos difusos. El rendimiento se evaluó mediante tres parámetros: exactitud, especificidad y sensibilidad. Resultados. El modelo desarrollado obtuvo un excelente desempeño predictivo, con una exactitud del 95 %. Además, permitió identificar el comportamiento de las variables involucradas usando iteraciones simuladas, lo que proporcionó información valiosa sobre la dinámica de los factores de riesgo asociados con la diabetes. Conclusiones. Los mapas cognitivos difusos demostraron ser de gran valor para la identificación temprana de la enfermedad y en la toma de decisiones clínicas. Los resultados sugieren el potencial de estos enfoques en aplicaciones clínicas relacionadas con la diabetes y respaldan su utilidad en la práctica médica para mejorar los resultados de los pacientes.
Introduction. Diabetes is a chronic disease characterized by a high blood glucose level. It can lead to complications that affect the quality of life and increase the costs of healthcare. In recent years, prevalence and mortality rates have increased worldwide. The development of models with high predictive performance can help in the early identification of the disease. Objective. To develope a model based on artificial intelligence to support clinical decision-making in the early detection of diabetes. Materials and methods. We conducted a cross-sectional study, using a dataset that contained age, signs, and symptoms of patients with diabetes and of healthy individuals. Pre-processing techniques were applied to the data. Subsequently, we built the model based on fuzzy cognitive maps. Performance was evaluated with three metrics: accuracy, specificity, and sensitivity. Results. The developed model obtained an excellent predictive performance with an accuracy of 95%. In addition, it allowed to identify the behavior of the variables involved using simulated iterations, which provided valuable information about the dynamics of the risk factors associated with diabetes. Conclusions. Fuzzy cognitive maps demonstrated a high value for the early identification of the disease and in clinical decision-making. The results suggest the potential of these approaches in clinical applications related to diabetes and support their usefulness in medical practice to improve patient outcomes.
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Innovative computer techniques are now being utilized not only in academic research but also in commercial dental practice, revolutionizing various areas of dentistry. This digitalization trend is driven by the increasing demands for treatment and diagnosis in the eld. Accurate diagnosis is crucial in dentistry, whether it be in orthodontics, maxillofacial surgery, periodontics, or prosthetics, as it forms the basis for creating effective treatment plans and restoring patients' oral health. While a specialist's expertise plays a vital role in diagnosis and treatment planning, it is susceptible to the inherent risks of human error, given the multifactorial nature of dental conditions. Consequently, there is growing interest in leveraging multi-parametric pattern recognition methods, including statistics, machine learning, and articial intelligence (AI), to enhance clinical decision-making. The introduction of clinical decision support systems (CDSS) and genetic algorithms (GAs) in dental research and clinical practice holds great promise for both healthcare professionals and patients. Extensive work has been undertaken to develop CDSS in dentistry, and this article reviews the latest advancements in this eld.
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In recent years, the artificial intelligence machine learning and deep learning technology have made leap progress. Using clinical decision support system for auxiliary diagnosis and treatment is the inevitable developing trend of wisdom medical. Clinicians tend to ignore the interpretability of models while pursuing its high accuracy, which leads to the lack of trust of users and hamper the application of clinical decision support system. From the perspective of explainable artificial intelligence, the authors make some preliminary exploration on the construction of clinical decision support system in the field of liver disease. While pursuing high accuracy of the model, the data governance techniques, intrinsic interpretability models, post-hoc visualization of complex models, design of human-computer interactions, providing knowledge map based on clinical guidelines and data sources are used to endow the system with interpretability.
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The clinical decision support system can provide medical staff with targeted patient diagnosis, treatment and care plan according to the recommendations of the guidelines, and assist medical staff to make clinical decisions. However, the adherence to clinical decision support system which based on guidelines was poor in clinical practice. Therefore, this article reviewed the influence factors of adherence to clinical decision support system which based on guideline from four aspects: system factors, individual factors, organizational factors and environmental factors, so as to improve the hindering factors and promote the application of clinical decision support system which based on guideline in future research and clinical practice.
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Objective:To study the practical efficacy of the clinical decision support system for diagnosis and treatment of thyroid cancer (CDSS-TC) in assisting doctors to complete several diagnosis and treatment tasks, and to make a preliminary evaluation of its clinical practicability according to the test results.Methods:From Jan. 2022 to Mar. 2022, 90 patients with thyroid cancer who were admitted to the Head and Neck Surgery Department of Shaw Hospital affiliated to Zhejiang University were prospectively analyzed, and the average time spent in reading the pre-operative B-ultrasound report, as well as the individual fitness of the dose adjustment of eugenol in 70 patients with thyroid cancer after surgery. A retrospective analysis was made of the compliance of the basis of the "recommended scheme" and the deviation of the basis of the doctor’s "final scheme" for the preoperative surgery of 120 patients with thyroid cancer who were treated for the first time in the head and neck surgery of Shaw Hospital affiliated to Zhejiang University from Mar. 2021 to May. 2021. All cases were treated by pure artificial (group A) and CDSS-TC assisted (group B) , and the differences in organization were compared.Results:The average time for disposal of a single B-ultrasound report in Group B was much shorter than that in Group A ( P=5.600E-04) ; The number of patients with excellent grade and the total number of patients with excellent grade and qualified grade recommended by the doctor in group B were significantly higher than those in group A ( P=7.819E-20 and P=1.335E-18) ; The conformity rate of the basis of CDSS-TC "Recommended Scheme" ≥ 98%; The deviation rate of the basis for "final protocol" of doctors in group B was lower than that in group A ( P=0.059 for total resection or not, P=0.075 for lateral neck dissection or not) . Conclusions:CDSS-TC can accurately extract the disease-related source information in all the original examination/laboratory reports, and provide accurate decision-making suggestions through efficient correlation analysis. In view of the accurate and objective conclusions of its analysis, it can provide high-quality and all-link decision support for doctors’ clinical diagnosis and treatment, and is an ideal information work platform.
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Abstract Background The pleura is a serous membrane that surrounds the lungs. The visceral surface secretes fluid into the serous cavity and the parietal surface ensures a regular absorption of this fluid. If this balance is disturbed, fluid accumulation occurs in the pleural space called "Pleural Effusion". Today, accurate diagnosis of pleural diseases is becoming more critical, as advances in treatment protocols have contributed positively to prognosis. Our aim is to perform computer-aided numerical analysis of Computed Tomography (CT) images from patients showing pleural effusion images on CT and to examine the prediction of malignant/benign distinction using deep learning by comparing with the cytology results. Methods The authors classified 408 CT images from 64 patients whose etiology of pleural effusion was investigated using the deep learning method. 378 of the images were used for the training of the system; 15 malignant and 15 benign CT images, which were not included in the training group, were used as the test. Results Among the 30 test images evaluated in the system; 14 of 15 malignant patients and 13 of 15 benign patients were estimated with correct diagnosis (PPD: 93.3%, NPD: 86.67%, Sensitivity: 87.5%, Specificity: 92.86%). Conclusion Advances in computer-aided diagnostic analysis of CT images and obtaining a pre-diagnosis of pleural fluid may reduce the need for interventional procedures by guiding physicians about which patients may have malignancies. Thus, it is cost and time-saving in patient management, allowing earlier diagnosis and treatment.
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Background: Health-related comorbidities often increase due to cancer among the ageing population. However, the domains of psychological functioning of geriatric patients remain undetected especially in the Indian scenario. This study aimed to evaluate psychological problems, perceived social support, fatigue, and quality of life among geriatric patients with cancer. Methods: A cross sectional study was conducted in a tertiary cancer center. Geriatric patients with cancer (n = 130) having solid malignancies categorized as older patients (>65 years) and younger geriatric patients (60–65 years) were included in the study. Depression, anxiety, perceived social support, fatigue, and quality of life was assessed using the Geriatric Depression Screening Scale, Geriatric Anxiety Scale, Multidimensional Scale of Perceived Social Support, Symbolic Assessment of Fatigue Extent, and the Old People Quality of life Scale, respectively. Descriptive and inferential statistics such as cross tab analysis, correlation and regression analysis. Results: A majority of patients 80 (61.5%) had low perceived social support, moderate-severe depression 61 (47.7%) and mild-moderate anxiety 55 (43.1%). Half of the patients were found to have poor quality of life. Further, psychological problems were higher among older geriatric patients (p = 0.000). Very few patients had a higher impact of fatigue on their daily functioning 17 (13.3%). There was a positive correlation between perceived social support, depression, anxiety, extent of fatigue, and quality of life (r = 0.256, P = 0.003). Conclusion: Psychological problems are higher among older geriatric patients with cancer undergoing treatment. Clinical implications could aim at regular screening to identify specific psychological issues and provide appropriate interventions. Future research warrants the efficacy of such therapeutic interventions for better quality of life outcomes
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Clinical decision support system based on medical artificial intelligence(AI)is a key link in medical artificial intelligence transformation of Alzheimer's disease.This paper reviews the status of medical AI used for diagnosis and treatment of Alzheimer's disease, proposed the deficiencies existing in the current application process, in order to provide new ideas for the development of a more professional clinical decision support system for Alzheimer's disease that is suitable for China's national conditions.
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Objective:To assess the predictors of outcomes for different subtypes of liver failure, and the effectiveness of artificial liver support systems in the treatment of liver failure.Methods:The clinical data of 112 patients with hepatitis B virus (HBV)- and non-HBV-related liver failure admitted to the intensive care unit (ICU) of the Fifth People's Hospital of Wuxi were collected from January to December 2020. The relevant etiologies of acute, subacute, acute-on-chronic, subacute-on-chronic, chronic subtype liver failure were analyzed. The efficacies of artificial liver support systems in the treatment of various subtypes of liver failure were also compared. The correlation of various indicators was analyzed by Spearman correlation analysis, the risk factors affecting the prognosis of patients with liver failure were analyzed by multivariate Logistic regression equation, and receiver operator characteristic curve (ROC curve) of subjects was plotted to evaluate the predictive value of each risk factor for the prognosis of patients with liver failure.Results:Among the 112 liver failure patients, 63 were caused by hepatitis B and 49 were caused by non-hepatitis B. The liver failure caused by hepatitis B was 6 times higher than for men than for women, which was higher than that of non-HBV liver failure group (1.33 times). Antithrombin Ⅲ (AT Ⅲ) and total bilirubin (TBil) levels of subacute liver failure were higher than those of pre-liver failure in the HBV liver failure group [AT Ⅲ: (59.33±14.57)% vs. (35.66±20.72)%, TBil (μmol/L): 399.21±112.94 vs. 206.08±126.96, both P < 0.05]. The levels of AT Ⅲ in patients with pre-liver failure and chronic liver failure in the non-HBV liver failure group were significantly higher than those with acute liver failure [(58.33±15.28%), (44.00±19.10)% vs. (31.33±7.57)%, both P < 0.05], patients with acute liver failure had significantly lower level of TBil than pre-liver failure (μmol/L: 107.83±49.73 vs. 286.20±128.92, P < 0.05), the TBil levels in patients with subacute and acute-on-chronic liver failure were also significantly higher than that in pre-liver failure group (μmol/L: 417.27±118.60, 373.00±187.00 vs. 286.20±128.92, both P < 0.05). Patients with subacute liver failure, subacute-on-chronic liver failure and chronic liver failure in the non-HBV failure group were significantly longer than those in acute liver failure (days: 36.00±8.31, 27.52±11.71, 27.72±22.71 vs. 11.00±1.41, all P < 0.05). There was no statistically significant difference in the case fatality rate of using the artificial liver support system between the HBV failure group and the non-HBV failure group (55.6% vs. 50.0%, P < 0.05), the levels of AT Ⅲ in the two groups of surviving patients were significantly higher than that of the dead [HBV liver failure group: (36.20±6.26)% vs. (27.33±8.87)%, non-HBV liver failure group: (41.06±4.16)% vs. (28.71±12.35)%, both P < 0.01]. Correlation analysis showed that there was a clear positive correlation between AT Ⅲ and TBil in the dead patients of HBV liver failure group and the survival and death patients of non-HBV liver failure group ( r values were 0.069, 0.341, 0.064, and P values were 0.723, 1.196 and 0.761, respectively); there was a significant inverse correlation between AT Ⅲ and TBil in the HBV liver failure group ( r = -0.105, P = 0.745). Multivariate Logistic regression analysis showed that AT Ⅲ was an independent risk factor affecting the prognosis of patients with non-HBV liver failure [odd ratio ( OR) = 1.023, 95% confidence interval (95% CI) was -0.001 to 0.001, P = 0.007]. TBil was an independent risk factor affecting prognosis of patients with HBV liver failure ( OR = 1.005, 95% CI was -0.002 to -7.543, P = 0.033). The analysis of ROC curve showed that AT Ⅲ had a predictive value for the prognosis of patients with non-HBV liver failure, the area under the ROC curve (AUC) = 0.747, the 95% CI was 0.592-0.902, P = 0.009. When the optimal truncation value was 39.5%, its sensitivity and specificity were 83.33% and 56.25%, respectively. Conclusions:Artificial liver support system treatment of liver failure was difficult to effectively reduce the mortality of patients with end-stage liver failure. In addition to AT Ⅲ, TBil also could be used as an indicator to assess liver compensatency and predict prognosis in liver failure patients.
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Objective:To evaluate the effectiveness of antimicrobial stewardship based on self-developed antibiotic clinical decision support system (aCDSS) in the inpatients at a tertiary hospital for consecutive 6 years, and to provide reference for rational use and antimicrobial stewardship.Methods:aCDSS was self-designed based on information technology and applied in clinical use in our hospital from 2015. Data of inpatient information and antibacterial use from January 2015 to December 2020 were collected from HIS and aCDSS. A retrospective study was conducted in all inpatients on the utilization rate and antibiotic use density.Results:Since 2015, with the comprehensive implementation of antimicrobial stewardship based on the aCDSS,there was a significant decline on the annual rate of antibiotic usage from 44.18% in 2015 to 38.70% in 2020, as well as on the usage rate of extended-spectrum antimicrobial agents including carbapenems, broad-spectrum β-lactam/β-lactamase inhibitors, tigecycline, broad-spectrum cephalosporins, fluoroquinolones, as well as glycopeptide and antifungal drugs. Compared with 2015, the usage of carbapenems, tigecycline and broad-spectrum β-lactam/β-lactamase inhibitors was declined nearly 50% in 2020, and the density of carbapenems and tigecycline were decreased by 29.6% and 7.1%, respectively in 2020. On the other side, the utilization rate and use density of narrow-spectrum cephalosporins continued to increase by year, the use density of narrow-spectrum cephalosporins accounting for 28.2% of all antibiotics in 2020.Conclusions:With the comprehensive implementation of aCDSS, the utilization rate and density of broad-spectrum and high-priced antibacterial drugs in our hospital have decreased continuously to decline in the past 6 years, while the proportion of narrow-spectrum antimicrobials has increased year by year, indicating that the structure of antimicrobial use has been continuously optimized and that antimicrobial stewardship based on the information technology have achieved remarkable results.
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Objective:To analyze the role of patient support system in multidrug-resistant/rifampicin-resistant tuberculosis (MDR/RR-TB) treatment adherence and outcome, and provide evidence for deepening the patient-centered support system.Methods:Based on the stakeholder analysis, definite stakeholders (administrators from the Department of Medical Insurance, and those from the provincial CDC), expectant stakeholders (administrators from regional CDC, health workers from primary CDCs, medical workers from designated MDR/RR-TB hospitals and MDR/RR-TB patients), and latent stakeholders (MDR/RR-TB patient families and their neighbors or colleagues) were selected using a purposive sampling. These stakeholders were subject to a semi-structured interview on patient support. The inclusion of participants ceased after reaching code or thematic saturation and meaning saturation, while thematic framework analysis was applied in interview data.Results:The 25 interviewees included could be categorized into three groups of stakeholders, i. e., 4 definite stakeholders, 19 expectant stakeholders and 2 latent stakeholders. Three themes summarized in this regard were definite stakeholders providing policy support to advance these patients′ access to standardized diagnosis and treatment services; diagnosis and treatment and management support of expectant stakeholders of these patients to encourage their compliance to treatment and enable their access to high quality medical care; and support from latent stakeholders as a critical guarantee for the patients to welcome a desirable treatment outcome. Psychological support provided under MDR/RR-TB basic care program in some provinces contributed positively to raising patients′ compliance. Economic support, treatment support from family menmbers ccould help the patients to welcome desirable outcomes.Conclusions:MDR/RR-TB patient-centered support system operating in the Yangtze River delta provide the patients with MDR/RR-TB diagnostic and treatment services of some accessibility. Given the progress, there are still shortcomings for the respective stakeholders to enhance their attention and collaboration to improve the access and equity to medical service.
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Objective:To explore the effect of the application of nursing decision support information system in the continuing nursing of stroke patients in convalescent period, and to provide guidance for the information-based whole process nursing of stroke patients in convalescent period.Methods:A total of 107 stroke patients in convalescent period admitted to 4 Grade Ⅲ Level A hospitals of Beijing city from March to November 2019 were selected. The patients were divided into control group (53 cases) and test group (54 cases) by coin tossing method. The control group followed uniformly formulated discharge health education manual for post-discharge management and follow-up, while the test group received health guidance and follow-up through the nursing decision support information system. Barthel Index and MOS SF-36 were used to evaluate the activities of daily living and quality of life of the two groups of patients before intervention and 3 and 6 months after the intervention, and the results were compared.Results:There was no significant difference in Barthel Index before the intervention between the two groups( P>0.05). After 3 months of intervention, the Barthel Index ≤ 49, 50-70 and ≥ 71 in the test group were 7, 17 and 27 cases respectively, and 16, 21 and 13 cases in the control group respectively, and the difference between the two groups was statistically significant ( Z=-2.95, P<0.01). After 6 months of intervention, the Barthel Index ≤ 49, 50-70 and ≥ 71 in the test group were 7, 12 and 32 cases respectively, and 10, 15 and 25 cases in the control group respectively,and the difference between the two groups was statistically significant ( Z=-2.21, P<0.05). There was no significant difference in MOS SF-36 before the intervention between the two groups( P>0.05). After 3 and 6 months of intervention, the total score of MOS SF-36 in the test group was (50.51 ± 14.57), (57.06 ± 14.85) respectively, and that in the control group was (42.02 ± 15.48), (45.58 ± 14.97) respectively, and the differences between the two groups were statistically significant ( t=2.84, 3.23, both P<0.05). Conclusions:The application of nursing decision support information system can effectively improve the daily life ability of patients, enhance the quality of life of patients.
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Objective:To analyze the application status and problems of clinical decision support system(CDSS) in medical institutions in China, and put forward corresponding suggestions.Methods:From April to May in 2020, a questionnaire survey was conducted in 1 013 medical institutions in 31 provinces of China. The contents of the questionnaire included the current situation of CDSS installation and deployment, the purpose of establishment, the source of knowledge base, the content to be optimized and the factors hindering the use.Results:199(19.64%) medical institutions had CDSS, among which 123 were used in the whole hospital and 76 in some departments; 426 medical institutions did not use CDSS, but had plans to use it. It was found that the current CDSS system had setbacks, such as big cognitive difference, lack of authority in knowledge, high difficulty in data governance, lack of industry standards and so on.Conclusions:In the future, the standardized use of CDSS in medical institutions could be promoted from the aspects of raising awareness, establishing knowledge authority and establishing standards.
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Objective:To explore the medication regularity and prescription rule of Chinese herbal medicine in the treatment of cardiac failure.Methods:The China Patent Publication Notice of the State Intellectual Property Office (http://epub.sipo.gov.cn/) was rearched and retrievedfor Chinese herbal medicine for the treatment of heart failure. The Traditional Chinese Medicine (TCM) inheritance support system (V 2.5) was used to input the prescription information and establish the database. The association rules, mutual information method, entropy clustering of complex systems and other data mining methods were used for commonly used drugs, combination rule and new prescription of core group.Results:A total of 101 prescriptions were included, involving 316 drugs. The frequency of commonly used drugs were Astragali Radix (59.41%), Poria (41.58%), Salviae Miltiorrhizae Radix et Rhizoma (40.59%), Descurainiae Semen Lepidii Semen (34.65%), Aconiti Lateralis Radix Praeparata (33.66%), and the medicinal properties were mainly warm, and the sweet taste. The main flavors weresweet, bitterness, and pungency, and the main sources of meridians belonged to liver, spleen, heart, lungs and kidneys. The most commonly used drug combinations contribute to supplement Qi, invigorate blood circulation and stasis, warm Yang, remove moisture. There were 12 core drug groups and 6 new prescriptions for heart failure. Conclusions:Analysis on formulas for heart failure shows that the prescriptions focus on supplementing qi and activating blood circulation, warming Yang reducing dampness, invigorating spleen, and nourishing Yin, dispel turbid, solid Yang. It can provide reference for clinical treatment to improve curative effect and standardize prescription medication.
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Objective:With the aid of the Inheritance Support System of Traditional Chinese Medicine V2.5 （TCMISS V2.5），to study the experience and prescription rules of professor WANG Jie in the treatment of frequent ventricular premature complexes，and inherit his clinical experience in diagnosis and treatment. Method:Professor WANG Jie's medical records and prescriptions for frequent ventricular premature complexes from 2016 to 2020 were collected and sorted out. Improved mutual information method，association rules，complex system entropy clustering，and unsupervised entropy hierarchical clustering were used to analyze the nature and flavor，channel tropism，concerted application rules，pair and combination of herbs for statistics， association rules analysis and discovery of new prescriptions. Result:A total of 122 prescriptions of professor WANG Jie on the treatment of frequent ventricular premature complexes were collected. 110 herbs，mostly with pungent and sweet flavors，were mainly on spleen channel and also on heart，kidney，liver，lung，and stomach channels. Cinnamomi Ramulus，Paeoniae Alba Radix<italic>，</italic>Os Draconis<italic>，</italic>Ostreae Concha<italic>， </italic>Glycyrrhizae Radix<italic>，</italic>and Jujubae Fructus<italic> </italic>had the highest frequency in use. The high-frequency herbal pair was Cinnamomi Ramulus-Paeoniae Alba Radix（116 times， accounting for 95.08%），the commonly used corner drugs were Cinnamomi Ramulus<italic>-</italic>Os Draconis<italic>-</italic>Ostreae Concha<italic> </italic>（108 times，88.52%），Cinnamomi Ramulus<italic>-</italic>Paeoniae Alba Radix<italic>-</italic>Ostreae Concha （106 times， 86.89%），Cinnamomi Ramulus<italic>-</italic>Paeoniae Alba Radix<italic>-</italic>Os Draconis （106 times，86.89%）. Commonly used herbal pair was<italic> </italic>Aucklandiae Radix-Amomi Villosi Fructus. The core prescription herbs included Cinnamomi Ramulus<italic>-</italic>Paeoniae Alba Radix<italic>-</italic>Os Draconis<italic>-</italic>Ostreae Concha<italic>-</italic>Glycyrrhizae Radix<italic>-</italic>Jujubae Fructus<italic>-</italic>Zingiberis Recens Rhizoma<italic>-</italic>Achyranthis Bidentatae Radix<italic>-</italic>Codonopsis Radix<italic>-</italic>Astragali Seu Hedysari Radix<italic>-</italic>Cistanches Herba-Poria<italic>-</italic>Ziziphi Spinosae Semen. Conclusion:Professor WANG Jie's prescription for the treatment of frequent ventricular premature complexes is Guizhi Jia Longgu Mulitang，and the main herbs are Cinnamomi Ramulus，Paeoniae Alba Radix，Os Draconis，Ostreae Concha，Glycyrrhizae Radix，and Jujubae Fructus. The final prescription could be adjusted according to the diseases and symptoms of patients.
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Objective:To select and evaluate new Chinese herbal prescription for the treatment of decreased ovarian reserve （DOR） and its appropriate dosage. Method:The literature concerning the treatment of DOR with traditional Chinese medicine （TCM） was retrieved from such databases as Chinese Journal Full-text Database， Wanfang Data Knowledge Service Platform， and Chongqing Weipu Database for Chinese Technical Periodicals （VIP）， based on which a database was established using the Traditional Chinese Medicine Inheritance Support System （TCMISS） V2.5. The data mining was then carried out to obtain the core combinations of Chinese herbs and new Chinese herbal prescription combinations， followed by the determination of the new Chinese herbal prescription by expert group discussion for experiment evaluation. The female SD rats were divided into the normal group， DOR model group， Kuntai capsule group， and low-， medium-， and high-dose new Chinese herbal prescription groups， with 12 rats in each group. Rats in the Kuntai capsule group and low-， medium-， and high-dose new Chinese herbal prescription groups were treated with Kuntai capsule solution （0.5 g·kg<sup>-1</sup> determined according to the dosage in the instruction） and 3.037 5， 6.075， and 9.12 g·kg<sup>-1</sup> new Chinese herbal prescription， respectively. After 21 days， the estrous cycle was observed by vaginal exfoliated cell smear， and the ovarian structure was observed by hematoxylin-eosin （HE） staining. The serum anti-mullerian hormone （AMH）， follicle stimulating hormone （FSH）， luteinizing hormone （LH）， and estrogen （E<sub>2</sub>） contents as well as the reactive oxygen species （ROS）， malondialdehyde （MDA）， and glutathione （GSH） levels and superoxide dismutase （SOD）， catalase （CAT）， and glutathione peroxidase （GSH-Px） activities in ovary were detected using biochemical methods. Result:The new Chinese herbal prescription subjected to experimental evaluation was composed of 11 Chinese herbs， namely Rehmanniae Radix Praeparata 20 g， Cervi Cornus Colla 12 g， Lycii Fructus 20 g， Corni Fructus 12 g， Albiziae Cortex 9 g， Nelumbinis Plumula 3 g， Salviae Miltiorrhizae Radix et Rhizoma 20 g， Astragali Radix 30 g， Atractylodis Macrocephalae Rhizoma 12 g， Dioscoreae Rhizoma 30 g， and Glycyrrhizae Radix et Rhizoma Praeparata Cum Melle 6 g. Compared with the model group， the Kuntai capsule group and medium- and high-dose new Chinese herbal prescription groups exhibited significantly improved estrous cycle and follicular development， elevated serum AMH and E<sub>2</sub> and ovarian GSH （<italic>P</italic><0.05）， decreased serum FSH and LH （<italic>P</italic><0.05） and ovarian ROS and MDA （<italic>P</italic><0.05）， and enhanced SOD， CAT， and GSH-Px activities （<italic>P</italic><0.05）. There were no significant differences in the above-mentioned indexes between the Kuntai capsule group and the middle- and high-dose new Chinese herbal prescription groups， but the estrous cycle and follicular development were better in the latter two groups. Conclusion:The new Chinese herbal prescription screened by data mining is able to enhance ovarian antioxidation， promote follicular development， ameliorate serum hormone and estrous cycle， and effectively improve ovarian reserve function in DOR rats. The medium dose （6.075 g·kg<sup>-1</sup>） has been proved optimal.
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@#Objective To verify the reliability of Anticlot Assistant, a patient self-management system for warfarin therapy assisted by artificial intelligence. Methods It was a single-center, prospective cohort study. The eligible 34 participants were recruited consecutively between November 29, 2017 to September 27, 2018 and managed by warfarin therapy via Anticlot Assistant. The recommendations of Anticlot Assistant were examined and verified by the doctors to ensure the security. Medical records were exported from the the background management system. An univariate analysis compared the outcomes between accepted and overridden records and a logistic regression model was built to determine independent predictors of the outcomes. The research team analyzed 153 medical records, which were from 18 participants and were input by 19 doctors. There were 97 records with doctor accepting the suggestion and 56 records with doctor rejecting the suggestion . Results When the doctors accepted the recommendations, the percentage of the next-test international normalized ratio (INR) in the therapeutic range was higher (64.95% vs. 44.64%, RR=2.298, 95%CI 1.173 to 4.499, P=0.014). The logistic regression analysis revealed that accepting the recommendations was an independent predictor for the next-test INR being in the therapeutic range after controlling potentially confounding factors (OR=2.446, 95%CI 1.103 to 5.423, P=0.028). Conclusion The algorithm of Anticlot Assistant is reasonable and reliable.
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RESUMO Os elevados custos e a limitação de recursos financeiros tornam essencial a priorização de projetos de saneamento. Os métodos multicritérios, para decisões individuais ou em grupo, são ferramentas modernas para hierarquizar portfólios de projetos. Há muitos métodos disponíveis na literatura técnico-científica. No Brasil, os Comitês das Bacias Hidrográficas constituem-se no ambiente para decisões descentralizadas sobre projetos nos âmbitos das bacias hidrográficas. Este artigo propôs um modelo multicritério de apoio à decisão para a priorização de um portfólio de projetos de saneamento no âmbito de um comitê de bacia. Como estudo de caso, utilizou-se um portfólio de 14 empreendimentos, objeto de um edital para aplicação de recursos financeiros do Fundo Estadual de Recursos Hídricos e/ou arrecadados pela cobrança da água bruta nas bacias dos rios Piracicaba, Capivari e Jundiaí. Empregou-se o método Preference Ranking Organization Method for Enrichment Evaluation II com a extensão gráfica Geometric Analysis for Interactive Aid. O modelo propiciou uma análise detalhada sobre as potencialidades das alternativas. Foi possível visualizar não somente a ordenação, mas também todas as propriedades de superação de cada alternativa pelas matrizes e pelos gráficos apresentados.
ABSTRACT High costs and limited financial resources make it essential to prioritize sanitation projects. Multicriteria methods, for individual or group decisions, constitute modern tools to rank project portfolios. Currently, there are many methods available in the scientific and technical literature. In Brazil, the Hydrographic Basin committees constitute the institution for decentralized decisions to manage projects portfolios. This article proposes a multicriteria model of decision support for prioritizing a portfolio of sanitation projects within the scope of a basin committee. As a case study, a portfolio of 14 projects is used, which is the subject of a public notice for the application of financial resources from FEHIDRO and/or collected by charging raw water in the Piracicaba, Capivari and Jundiaí (PCJ) basins. The method Promethee II was used with the graphic extension GAIA. The model provided a detailed analysis of the potentialities of the alternatives. It was possible to visualize not only the ordering, but also all the overcoming properties of each alternative by the matrices and the graphs presented.
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To dig out and analyze the drug rule of COVID-19 prevention prescriptions from provinces and cities by using Traditional Chinese Medicine Inheritance Support System, summarize and explore its potential new prescription. The Chinese medicine prevention programs for COVID-19 were collected and searched from the official website of the Health Commission and State Administration Medicine of Traditional Chinese Medicine of the country and provinces, autonomous regions, and municipalities. TCM prevention programs in 17 provinces including Heilongjiang, Beijing, Tianjin, Hebei, Henan, Jiangxi, Sichuan, Hubei, and Hunan, etc were received. A total of 82 herbs were included in 64 prescriptions, the most frequently used Chinese herbs were Astragalus membranaceus, Lonicera japonica, etc. Tonifying deficiency drugs with sweet and warm natures were used the most, the Chinese herbs distributed in the lung channel was the most in channel tropism drugs. Analysis by association rule, eight combinations of commonly used drugs were obtained. Based on entropy clustering method rule analysis, seven potential new prescriptions were obtained. Tonifying deficiency drugs are often used in various places to prevent COVID-19, focusing on the lung, spleen and stomach. Although the specific details are different, they all reflect the preventive thinking of traditional Chinese medicine.
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Objective: To summarize the prescription rules of traditional Chinese medicine (TCM) for treating alcoholic liver disease (ALD) based on TCM inheritance support system (V2.50). Methods: The literatures about TCM prescriptions for treating ALD were collected from CNKI, Wanfang database, and VIP database. The TCM inheritance platform system was used to analyze the prescription rules of TCM in the treatment of alcoholic liver disease. Results: Statistics showed that the majority of prescriptions were used to treat alcoholic fatty liver, alcoholic hepatitis, and alcoholic cirrhosis. Through "frequency statistics" analysis, 107 prescriptions were found involving 149 flavors of TCM, with a cumulative frequency of 1 195 times. Twenty-three Chinese medicines with a frequency of ≥ 15 times were used, and the cumulative frequency was 737 times (62%). The most frequently used medicines were blood-activating and stasis-removing drugs, water-diffusing and damp-permeating drugs, tonics, heat-clearing drugs, antialcoholic poisons and qi-regulating drugs. The commonly used doses of Salvia miltiorrhiza, Poria cocos, Bupleurum chinense, Glycyrrhiza uralensis, Atractylodes macrocephala, Alismatis Rhizoma, and Curcumae Radix in the top 10 medicines ranked in the frequency of medication accorded with the prescribed doses in the Pharmacopoeia of the People's Republic of China (2015 edition), while Crataegi Fructus, Artemisiae Scopariae Herba, and Puerariae Lobatae Radix exceeded the prescribed doses. In the frequency analysis of drug pairs, the combination of S.miltiorrhiza and B. chinense was the most widely used. According to the association rules of drug combination, the correlation between Curcumae Radix and S. miltiorrhiza was the strongest, that was, the probability of S. miltiorrhiza appearing with the emergence of Curcumae Radix was 88%. From the network display chart, it was indicated that S. miltiorrhiza and P. cocos were the main herbs for treatment. Through unsupervised entropy hierarchical clustering algorithm, 14 core combinations for new clustering were extracted, and seven new prescriptions can be obtained by further clustering. Conclusion: The basic principles of TCM treatment of ALD include promoting blood circulation and removing blood stasis, removing dampness, tonifying, detoxifying alcohol, and promoting qi, and with "protecting spleen and stomach function" as its purpose, which accords with the theoretical basis of traditional Chinese medicine in treating alcoholic liver disease. Core combinations and new prescriptions provide references for clinical drug use and new drug research and development, but new prescriptions must be further evaluated with the combination of traditional Chinese medicine theory and clinical practice.