Out of hospital cardiac arrest, first steps to know and follow in Mexico to have cardioprotected territories. A point of view of a group of experts / Paro cardiaco extrahospitalario, primeros pasos que se deben conocer y hacer en México para tener espacios cardioprotegidos. Punto de vista de un grupo de expertos

Abstract Sudden cardiac death is a common occurrence. Out-of-hospital cardiac arrest is a global public health problem suffered by ≈3.8 million people annually. Progress has been made in the knowledge of this disease, its prevention, and treatment; however, most events occur in people without a previous diagnosis of heart disease. Due to its multifactorial and complex nature, it represents a challenge in public health, so it led us to work in a consensus to achieve the implementation of cardioprotected areas in Mexico as a priority mechanism to treat these events. Public access cardiopulmonary resuscitation (CPR) and early defibrillation require training of non-medical personnel, who are usually the first responders in the chain of survival. They should be able to establish a basic and efficient CPR and use of the automatic external defibrillator (AED) until the emergency services arrive at the scene of the incident. Some of the current problems in Mexico and alternative solutions for them are addressed in the present work.

Resumen La muerte súbita cardíaca (SCD) es un acontecimiento común. El paro cardiaco extrahospitalario (OHCA) es un problema de salud pública mundial que sufren ≈3.8 millones de personas al año. Se ha avanzado en el conocimiento de esta enfermedad, su prevención y tratamiento, sin embargo, la mayoría de los eventos se producen en personas sin diagnóstico previo de cardiopatía. Debido a su carácter multifactorial y complejo, representa un reto en salud pública, lo que obliga a trabajar en un consenso para lograr la implementación de "Espacios Cardio protegidos" en México, como mecanismo prioritario de atención a estos eventos. La reanimación cardiopulmonar básica (RCPB) y la desfibrilación temprana de acceso público requieren de entrenamiento al personal no médico, que suelen ser los primeros respondientes para iniciar la cadena de la supervivencia. Ellos deberían instaurar una RCPB eficiente y el uso del desfibrilador automático externo (AED) hasta que lleguen al lugar del incidente los servicios de emergencias. El presente trabajo menciona algunos de los problemas actuales en México y algunas opciones de solución para los mismos.

Automatic detection and classification of disease in citrus fruit and leaves using a customized CNN based model / Detección y clasificación automática de enfermedades en frutas y hojas de cítricos utilizando un modelo basado en CNN personalizado

India's commercial advancement and development depend heavily on agriculture. A common fruit grown in tropical settings is citrus. A professional judgment is required while analyzing an illness because different diseases have slight variati ons in their symptoms. In order to recognize and classify diseases in citrus fruits and leaves, a customized CNN - based approach that links CNN with LSTM was developed in this research. By using a CNN - based method, it is possible to automatically differenti ate from healthier fruits and leaves and those that have diseases such fruit blight, fruit greening, fruit scab, and melanoses. In terms of performance, the proposed approach achieves 96% accuracy, 98% sensitivity, 96% Recall, and an F1 - score of 92% for ci trus fruit and leave identification and classification and the proposed method was compared with KNN, SVM, and CNN and concluded that the proposed CNN - based model is more accurate and effective at identifying illnesses in citrus fruits and leaves.

El avance y desarrollo comercial de India dependen en gran medida de la agricultura. Un tipo de fruta comunmente cultivada en en tornos tropicales es el cítrico. Se requiere un juicio profesional al analizar una enfermedad porque diferentes enfermedades tienen ligeras variaciones en sus síntomas. Para reconocer y clasificar enfermedades en frutas y hojas de cítricos, se desarrolló e n esta investigación un enfoque personalizado basado en CNN que vincula CNN con LSTM. Al utilizar un método basado en CNN, es posible diferenciar automáticamente entre frutas y hojas más saludables y aquellas que tienen enfermedades como la plaga de frutas , el verdor de frutas, la sarna de frutas y las melanosis. En términos de desempeño, el enfoque propuesto alcanza una precisión del 96%, una sensibilidad del 98%, una recuperación del 96% y una puntuación F1 del 92% para la identificación y clasificación d e frutas y hojas de cítricos, y el método propuesto se comparó con KNN, SVM y CNN y se concluyó que el modelo basado en CNN propuesto es más preciso y efectivo para identificar enfermedades en frutas y hojas de cítricos.

Separation and Enrichment of β-Agonists from Animal Livers Based on Magnetic Solid-Phase Extraction with Automated-treatment Device / 分析化学

A liquid chromatography-tandem mass spectrometry(LC-MS/MS)method was developed for determination of three kinds of β-agonists(Clenbuterol(CL),Ractopamine(RAC)and Salbutamol(SAL))residues in animal liver samples.The liver sample homogenates were extracted with organic solvent,followed by clean-up using the automatic magnetic solid-phase extraction(MSPE),and then analyzed using LC-MS/MS.The results showed that the magnetic mixed-mode cation exchange adsorbent(M-MCX)exhibited 34%higher adsorption capacity than the conventional mixed-mode cation exchange(MCX)column.Furthermore,the clean-up was conducted by using an automatic MSPE device,and 8 samples could be simultaneously treated within 30 min.The limits of detection(LOD)were 0.01-0.1 μg/kg,the average recoveries ranged from 88.2%to 110.5%,and the relative standard deviations(RSDs)were in range of 2.9%-10.3%at three spiked levels for the three kinds of β-agonists.Compared with the traditional SPE technique,the present method had many advantages such as simple operation,rapidity and high efficiency,which was suitable for high-throughput and automatic detection of residues in routine analysis.

Feasibility study on automatic segmentation of pelvic intestinal tube for radiotherapy images based on deep learning / 复旦学报（医学版）

Objective To study the feasibility on automatic contouring of pelvic intestinal tube based on deep learning for radiotherapy images.Methods A total of 100 patients with diagnosis of rectal cancer,received radiotherapy in Zhongshan Hospital,Fudan University from 2019 to 2021,were randomly selected.Sixty cases were randomly enrolled to train the models,and the other 40 cases were applied to test.Based on the original small intestine model in automatic segmentation software AccuContour,60,40 and 20(2 groups)cases in the model cases were used to train the models Rec60,Rec40,Rec20A and Rec20B with manual contouring as ground truth.Other 40 cases for test were applied to evaluate the Dice similarity coefficient(DSC),95%Hausdorff distance(HD95)and average symmetric surface distance(ASSD)between the manual contouring and original model along with model Rec60.The DSC of the 5 groups of auto-segmentations were compared as well.The paired t tests were performed for each pair of the original model and 4 trained models.Results The small bowel contoured by trained models were more similar to the manual contouring.They could distinguish the boundary of the intestinal tube better and distinguish the small bowel from the colon.The average DSC,HD95 and ASSD of Rec60 were 0.16 higher(P＜0.001),12.4 lower(P＜0.001)and 5.14 lower(P＜0.001)than the original model respectively.According to the paired t tests,there were no statistical differences in DSC between the 4 training models and the original model.No statistical difference was observed between Rec60 and Rec40,while they were both significantly different from the two Rec20 models.There was no statistical difference between Rec20B and Rec20B.Conclusion For radiotherapy images,model training can effectively improve the accuracy of intestinal tube delineation.Forty cases were enough for training an optimal model of automatic segmentation for pelvic intestinal tube in AccuContour software.

Feasibility of automatic segmentation of CTV and OARs in postoperative radiotherapy for cervical cancer using AccuLearning / 实用医学杂志

Objective To explore the feasibility of automatic segmentation of clinical target volume(CTV)and organs at risk(OARs)for cervical cancer using AccuLearning(AL)based on geometric and dosimetric indices.Methods Seventy-five CT localization images with manual contouring data of postoperative cervical cancer were enrolled in this study.Sixty cases were randomly selected to trained to generate automatic segmentation model by AL,and the CTV and OARs of the remaining 15 cases were automatically contoured.Radiotherapy plans on the automatic segmentation contours were imported on the CT images of manual contours.The efficiency,Dice similarity coefficient(DSC),Hausdorff distance(HD)and dosimetric parameters were compared between the two methods.Results The time of automatic segmentation was significantly shorter than that of the manual contour(P<0.05).The DSC of all structures were≥0.87.The HD of bowel bag and rectum were about 10 mm,and that of the rest of OARs were less than 5 mm.CTV(D98,V90% ,V95% ,Dmean,HI),bowel bag(V50)and bladder(V50)had significant differences in dosimetric comparison(P<0.05).Conclusion The automatic segmentation model based on AL can improve the efficiency of radiotherapy.Automatic segmentation of OARs has the potential of clinical application,while that of CTV still needs to be further modified.

Analysis of the characteristics and risk factors of levofloxacin-induced arrhythmias / 药物流行病学杂志

Objective To investigate the characteristics,clinical indicators and risk factors of levofloxacin-induced arrhythmias in large hospitalized populations.Methods Using the"Adverse Event Active Monitoring and Intelligent Assessment Alert System-Ⅱ"(ADE-ASAS-Ⅱ),the electronic medical record of inpatients using levofloxacin in 2019 was monitored to obtain relevant data for patients with arrhythmias.Patients without arrhythmia were selected by propensity score matching,and the risk factors of levofloxacin-induced arrhythmias were analyzed by univariate and multivariate conditional logistic regression.Results The incidence of levofloxacin-induced arrhythmias was 1.64％in 12 879 people who used levofloxacin.The incidence in people over 65 years was 3.22％.The main manifestations of levofloxacin-induced arrhythmias were extrasystole(0.84％),tachycardia(0.63％),QT interval prolongation(0.44％),and no severe arrhythmias such as torsades de pointes and ventricular fibrillation.Multivariate Logistic regression analysis showed that the course of administration(OR=1.030,95％CI 1.009 to 1.050,P=0.004)and intravenous administration(OR=2.392,95％CI 1.478 to 3.870,P＜0.001)independent risk factors for levofloxacin-induced arrhythmias.Conclusion Arrhythmias caused by levofloxacin are common and have various types,among which the occurrence of QT interval prolongation is occasional.We should pay more attention to elderly patients who receive intravenous levofloxacin and try to avoid long courses of medication.

An Exploratory Study of Multimodality in Medical Imaging and Natural Language Processing / 医学信息学杂志

Purpose/Significance Achieving automatic generation of medical imaging reports is important for reducing the workload of radiologists and promoting the standardization of clinical workflow.Method/Process Focusing on finding the chest report generation mod-els with open source code in recent years,the paper develops an automatic medical image report generation method based on the CDGPT2 model.Result/Conclusion The advantages of the model in report generation are still to be explored,the quality of reports generated after modifications to the decoder inputs of the model is not high.Future research could improve the performance of the model by using large datasets and incorporating more clinical information.

Methodological evaluation of automatic iodine detector for measuring urinary iodine / 中华地方病学杂志

Objective:To evaluate the feasibility of using an automatic iodine detector to detect urinary iodine.Methods:Using an automatic iodine detector to determine urinary iodine, within the range of the 50 - 1 000 μg/L standard curve, methodological evaluations on the linear relationship of the standard curve, precision, and accuracy (determination of urinary iodine standard substances GBW09108x, GBW09110c, GBW09111b, GBW09112b, and spiked recovery experiments) were conducted. Method comparison experiments with the arsenic cerium catalytic spectrophotometry recommended by the National Reference Laboratory for Iodine Deficiency Disorders (NRL) was conducted.Results:The method has a good linear relationship within the range of 50 - 1 000 μg/L standard curve, │ r│ > 0.999 0. The coefficient variations for measuring iodine levels in urine samples with low, medium, and high iodine concentrations were 2.4%, 0.8%, and 1.1%, respectively. The recovery rates of urine samples with low, medium, and high iodine concentrations ranged from 93.0% to 104.1%, with a total average recovery rate of 98.9%. The determination results of standard substances GBW09108x, GBW09110c, GBW09111b, and GBW09112b were all within the given standard value ± uncertainty range [(80.8 ± 9.0), (227.0 ± 15.0), (525.0 ± 17.0), (794.0 ± 28.0) μg/L]. There was no statistically significant difference between the results obtained by using the iodine automatic detector and the NRL recommended standard method ( t = - 1.94, P = 0.062). Conclusions:The iodine automatic detector has a high degree of automation, strong environmental adaptability, and excellent detection efficiency in determining urinary iodine. The experimental results of methodological characteristics are good and can be used for the detection of urinary iodine samples.

Relation between dysfunctional attitude and depressive symptoms in adolescents： the acting path of negative automatic thoughts and positive coping style / 四川精神卫生

BackgroundThe prevalence of depressive disorder in adolescents is on the rise. There have been studies on the pairwise relations between dysfunctional attitude， negative automatic thoughts， positive coping style and depressive symptoms in the past. However， the impact of the intrinsic relations among dysfunctional attitude， negative automatic thoughts and positive coping style on depressive symptoms is still unclear. ObjectiveTo explore the influence of dysfunctional attitude on adolescent depressive symptoms and examine the action path of negative automatic thoughts and positive coping style on it， in order to provide references for intervention for adolescent patients with depressisve disorder. MethodsThis study involved 162 adolescent patients with depressive disorder， who met the diagnostic criteria for depressive episodes in the International Classification of Diseases， 10th edition （ICD-10） and received treatment in Taiyuan Psychiatric Hospital from October 1， 2022 to October 31， 2023. These patients were evaluated using Self-rating Depression Scale （SDS）， Dysfunction Attitude Scale （DAS）， Positive Coping Style Subscale in Simplified Coping Style Questionnaire（SCSQ） and Automatic Thoughts Questionnaire （ATQ）. Pearson correlation analysis was adopted to examine the correlation among scores of scales above. Model 6 in Process 3.4.1 was adopted to test the acting path of negative automatic thoughts and positive coping style between dysfunctional attitude and adolescent depression symptoms. ResultsA total of 148 adolescent patients with depressive disorder completed an effective questionnaire survey， with a response rate of 91.36%. The direct effect value of dysfunctional attitude on depressive symptoms was 0.423 and the effect size was 63.32%. Negative automatic thoughts and positive coping style affected as acting path between dysfunctional attitude and depressive symptoms， with effect values of 0.156 （accounting for 23.35% of the total effect） and 0.045 （accounting for 6.74% of the total effect） respectively. Meanwhile， negative automatic thoughts and positive coping style affected as a chain reaction pathway between dysfunctional attitude and depressive symptoms， with an effect value of 0.044， accounting for 6.59% of the total effect. ConclusionDysfunctional attitude can not only directly affect the depressive symptoms of adolescent patients with depressive disorder， but also affect the depressive symptoms of adolescent patients with depressive disorder through the independent path or chain path of negative automatic thoughts and positive coping style.

YOLOX target detection model for automatically identifying endovascular interventional instruments on images of digital subtract angiography / 中国介入影像与治疗学

Objective To observe the value of a YOLOX target detection model for automatically identifying endovascular interventional instruments on images of digital subtract angiography(DSA).Methods DSA data of 37 patients who underwent abdominal endovascular interventional therapy were retrospectively analyzed.Totally 4 435 DSA images were captured and taken as data set,which were divided into training set(n=3 991)and verification set(n=444)at the ratio of 9∶1.Six kinds of endovascular interventional instruments were labeled.YOLOX algorithm was applied for deep learning of data in training set in order to build a target detection model,and the efficacy of the model for automatically identifying endovascular interventional instruments on DSA images was evaluated based on varification set.Results A total of 6 668 labels were put on 4 435 DSA images,aimed on Terumo 0.035in loach guide wire(n=587),Cook Lunderquist super hard guide wire(n=990),Optimed 5F with graduated pig tail catheter(n=1 680),Cordis MPA multi-functional catheter(n=667),Boston Scientific V-18 controllable guide wire(n=1 330)and Terumo 6F long sheath(n= 1 414),respectively.The training set contained 527,875,1 466,598,1 185 and 1 282,while the verification set contained 60,115,214,69,145 and 132 the above labels,respectively.The pixel accuracy of YOLOX target detection model for automatically identifying the above instruments in the verification set was 95.23%,97.32%,99.18%,98.97%,97.60%and 98.19%,respectively,with a mean pixel accuracy of 97.75%.Conclusion YOLOX target detection model could automatically identify endovascular interventional instruments on images of DSA.

Consistency and Repeatability of Cerebral Blood Flow by Automatic Segmentation of Region of Interest and 3D-pCASL Fusion in Hippocampal Subregions / 中国医学影像学杂志

Purpose To evaluate the consistency and repeatability of cerebral blood flow(CBF)values measured by automatic segmentation of region of interest(ROI)and arterial spin labeling(ASL)functional image fusion in hippocampal sclerosis patients with medial temporal lobe epilepsy.Materials and Methods From January 2021 to October 2022,a total of 52 patients with medial temporal lobe epilepsy confirmed by MRI or pathology in General Hospital of Ningxia Medical University were retrospectively collected.All subjects were scanned on 3.0T MRI to obtain axial T1 weighted three-dimensional magnetization reserve gradient echo(3D-T1W1-MPGAGE)sequence and three-dimensional pseudo continuous ASL sequence.The 3D-T1W1-MPGAGE imaging were automatically segmented.Two physicians used the freeview visualization interface of freeSurfer software to fuse the ROI and ASL functional images of the hippocampal subregions and to measure the CBF values.The intra-observer and inter-observer consistency and repeatability were evaluated and analyzed.The consistency analysis and repeatability evaluation were performed via intraclass correlation coefficient(ICC),Bland-Altman diagram and Wilcoxon rank sum test.Results The ICC of CBF values measured by two physicians were all>0.750,with an average of 0.868±0.095.The ICC of left and right hippocampal subregions were as follows:subiculum(SUB):0.818/0.801,cornu ammonis(CA)1:0.920/0.907,CA2-3:0.759/0.978,CA4:0.757/0.758 and dentate gyrus(DG):0.990/0.991;The ICC delineated by the same physician's ROI were all>0.990 with an average of 0.994±0.002.The ICC of left and right hippocampal subregions were as follows:SUB:0.993/0.993,CA1:0.996/0.995,CA2-3:0.989/0.994,CA4:0.992/0.995 and DG:0.993/0.996.The Bland-Altman diagram showed the scatter distribution and consistency,and the coefficient of repeatability was obtained.The same observer had certain repeatability for the fusion measurement of automatic segmentation ROI and ASL functional images.Conclusion The CBF values measured by fusing ROI and ASL functional images of automatically segmented hippocampal subregion have higher consistency and repeatability.

Application of a deep learning-based three-phase CT image models for the automatic segmentation of gross tumor volumes in nasopharyngeal carcinoma / 中华放射医学与防护杂志

Objective:To investigate the effectiveness and feasibility of a 3D U-Net in conjunction with a three-phase CT image segmentation model in the automatic segmentation of GTVnx and GTVnd in nasopharyngeal carcinoma.Methods:A total of 645 sets of computed tomography (CT) images were retrospectively collected from 215 nasopharyngeal carcinoma cases, including three phases: plain scan (CT), contrast-enhanced CT (CTC), and delayed CT (CTD). The dataset was grouped into a training set consisting of 172 cases and a test set comprising 43 cases using the random number table method. Meanwhile, six experimental groups, A1, A2, A3, A4, B1, and B2, were established. Among them, the former four groups used only CT, only CTC, only CTD, and all three phases, respectively. The B1 and B2 groups used phase fine-tuning CTC models. The Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD95) served as quantitative evaluation indicators.Results:Compared to only monophasic CT (group A1/A2/A3), triphasic CT (group A4) yielded better result in the automatic segmentation of GTVnd (DSC: 0.67 vs. 0.61, 0.64, 0.64; t = 7.48, 3.27, 4.84, P < 0.01; HD95: 36.45 vs. 79.23, 59.55, 65.17; t = 5.24, 2.99, 3.89, P < 0.01), with statistically significant differences ( P < 0.01). However, triphasic CT (group A4) showed no significant enhancement in the automatic segmentation of GTVnx compared to monophasic CT (group A1/A2/A3) (DSC: 0.73 vs. 0.74, 0.74, 0.73; HD95: 14.17 mm vs. 8.06, 8.11, 8.10 mm), with no statistically significant difference ( P > 0.05). For the automatic segmentation of GTVnd, group B1/B2 showed higher automatic segmentation accuracy compared to group A1 (DSC: 0.63, 0.63 vs. 0.61, t = 4.10, 3.03, P<0.01; HD95: 58.11, 50.31 mm vs. 79.23 mm, t = 2.75, 3.10, P < 0.01). Conclusions:Triphasic CT scanning can improve the automatic segmentation of the GTVnd in nasopharyngeal carcinoma. Additionally, phase fine-tuning models can enhance the automatic segmentation accuracy of the GTVnd on plain CT images.

Performance evaluation of Ethos intelligent optimization engine in automatic plan generation / 中华放射肿瘤学杂志

Objective:To evaluate the automatic optimization performance and clinical feasibility of the intelligent optimization engine (IOE) in the Ethos online adaptive radiotherapy platform.Methods:Clinical data of 11 patients with postoperative cervical cancer treated with Halcyon accelerator were retrospectively analyzed. Manual planning was performed for all patients using the 4 full arc volumetric modulated arc therapy (VMAT) (Manual-4Arc) in Eclipse, with a prescription dose of 45 Gy/25F. Patient images and structures were imported into the Ethos simulator, and appropriate clinical goals were added based on clinical requirements. The target coverage was normalized to 95%. Automatic plan generation was conducted using IOE, resulting in 7, 9, and 12 field intensity modulated radiotherapy (IMRT) plans (IMRT-7F、IMRT-9F、IMRT-12F), as well as 2 and 3 arc VMAT plans (VMAT-2Arc、VMAT-3Arc). Dosimetric index comparisons were made between the Manual-4Arc plans and the 5 groups of IOE-generated plans through one-way analysis of variance. Based on the analysis results, Turky post hoc multiple comparisons were performed to evaluate the automatic optimization performance of IOE.Results:In terms of the high dose area, the IMRT-12F plans showed the lowest D 1% for the planning target volume (PTV), and there were significant differences compared to the Manual-4Arc plans ( P=0.004). Regarding target coverage, all groups produced clinical target volume (CTV) plans that met the clinical requirements. Although the Ethos online adaptive plans were normalized during planning, the PTV coverage was slightly insufficient. For organs at risk (OAR) close to the target, such as the bladder, there were significant differences in V 30 Gy, V 40 Gy, and D mean among the 6 groups of plans. The dose ranking for the bladder was generally as follows: IMRT-12F<IMRT-9F<Manual-4Arc<IMRT-7F<VMAT-3Arc<VMAT-2Arc. There were significant statistical differences in V 30 Gy and D mean for the rectum, and the dose ranking was generally consistent with that of the bladder, except for a switch between the IMRT-7F and Manual-4Arc plans. There were no significant differences in rectal V 40 Gy, small intestine D max, and D mean among the 6 groups of plans. For OAR distant from the target, such as the left and right femoral heads, spinal cord, and bone marrow, the dose ranking was generally as follows: IMRT-12F<IMRT-9F<IMRT-7F<VMAT-2Arc<VMAT-3Arc<Manual-4Arc. Conclusion:The plans automatically generated by Ethos IOE in postoperative patients with cervical cancer can achieve similar performance to manual plans, and the automatically generated IMRT-12F and IMRT-9F plans are recommended for clinical use.

Establishment and validation of a dose-response curve for semi-automatic analysis of dicentric chromosomes / 中国职业医学

ObjectiveTo establish a dose-effect curve for semi-automatic analysis of dicentric chromosomes(DC) based on an automatic chromosome analysis system. Methods A total of three healthy volunteers were recruited as the study subjects, and their peripheral blood was collected and stimulated by X-ray at doses of 0.00, 0.10, 0.25, 0.50, 0.75, 1.00, 2.00, 3.00, 4.00, and 5.00 Gy, with the absorbed dose rate of 1.0 Gy/min. Images of DC in the mid-stage of cell division were collected using a high-throughput automatic chromosome analysis system. The DCScore software was used to automatically analyze DC aberrations, and a dose-effect curve for semi-automatic analysis of DC was fitted after manual confirmation. The fitted dose-effect curve for semi-automatic analysis of DC was validated for accuracy using three proficiency test samples from the national quality assessment of biological dose. Results The incidence of DC increased with increasing irradiation doses in the range of 0.00-5.00 Gy (P<0.01). The dose-effect curve for the fitted semi-automatic analysis of DC was ŷ =0.000 8 (±0.000 2) +0.009 2(±0.000 9) D+0.014 2(±0.000 4) D2 (R2= 0.999 8). The relative deviation between the estimated dose and the actual dose of the three test samples was about 20.00%, indicating curve applicability for biological dose estimation. Moreover, excluding the time spent on manual analysis, the semi-automatic analysis method increased the analysis efficiency by 26.0 times. Conclusion The semi-automatic analysis dose-effect curve for DC stimulated by X-ray is constructed for biological dose estimation, which can reduce the manual analysis time, and holds great potential for application in nuclear emergency response to large-scale radiation accidents.

Impacto de la Inteligencia Artificial en la Radiología

Introducción: El creciente desarrollo computacional ocurrido en los últimos años, así como el acceso a gran número de datos (Big Data) ha posibilitado la explotación de los recursos informáticos para el desarrollo de algoritmos que aumentan la calidad y alcance de la inteligencia artificial (IA), la cual está tomando un rol central en la radiología. Objetivo: Analizar el impacto de la Inteligencia Artificial en la Radiología y la necesidad de implementación en los servicios de imagenología. Método: Se emplearon 23 referencias bibliográficas en inglés y español, la mayoría extraídas de PubMed, SciELO y ScienceDirect usando los descriptores "Inteligencia Artificial", "Radiología" y "Aprendizaje automático" en idioma español y "Artificial Intelligence", "Radiology" y "Machine Learning" para el inglés. Desarrollo: No existe área de la Radiología en la cual no se haya implementado la inteligencia artificial, con el fin de mejorar y desarrollar programas que le faciliten al radiólogo y al técnico, la obtención y diagnóstico de imágenes. Cuba también está inmersa en este proceso; se están dando los primeros pasos por el desarrollo de estas tecnologías. Conclusiones: La investigación, optimización de flujo de trabajo, radiómica, predicción y clasificación de imágenes son beneficios que nos aporta la IA; lograr un aumento en la calidad de estos procesos solo es posible a través de la alianza entre las ciencias médicas e informáticas.

Introduction: The growing computational development that has occurred in recent years, as well as the access to a large number of data (Big Data), has made the exploitation of computing resources possible to develop algorithms that increase the quality and scope of artificial intelligence (AI), which is taking a central role in radiology. Objective: To analyze the impact of artificial intelligence in radiology and the need for its implementation in imaging services. Method: A total of 23 bibliographical references in English and Spanish, most of them obtained from PubMed, SciELO and ScienceDirect databases, were analyzed using descriptors such as "inteligencia artificial", "radiología" and "aprendizaje automático" for the Spanish language and "artificial intelligence", "radiology" and "machine learning" for the English language. Results: There is no area of ​​Radiology in which artificial intelligence has not been implemented in order to improve and develop programs that make it easier for the radiologist and the technician to obtain and diagnose images. Cuba is also immersed in this process; the first steps are being taken towards the development of these technologies. Conclusions: Research, workflow optimization, radiomics, prediction and classification of images are benefits that AI brings us; achieving an increase in the quality of these processes is only possible through the alliance between medical and computer sciences.

Comprobación del control automático de exposición en el tomógrafo Canon Aquilion ONE / Verification of the automatic exposure control on the Canon Aquilion ONE tomograph

Resumen Dado el uso incrementado de la tomografía computarizada en la Caja Costarricense del Seguro Social durante los últimos 10 años, se ha vuelto cada vez más importante obtener imágenes de la calidad diagnóstica requerida con la mínima dosis de radiación posible al paciente. Para lograr esto, en los sistemas de tomografía computarizada se utiliza, rutinariamente, el control automático de exposición, el cual modula la corriente del tubo según la atenuación del haz que produce el paciente y que se obtiene en el escanograma. Objetivo: Comprobar el funcionamiento del control automático de exposición de un tomógrafo Canon Aquilion ONE en la dosis suministrada al paciente y verificar la importancia de realizar un simple o doble escanograma para diferentes protocolos clínicos. Métodos: Se analizó el comportamiento de la dosis, el ruido y la intensidad de la corriente obtenida en un maniquí con diferentes secciones elípticas que varían sus dimensiones en los ejes X-Y. Se determinó el producto dosis longitud en diferentes protocolos clínicos con el control automático de exposición activado debido a un simple o doble escanograma. Resultados: Para intensidades de corrientes fijas, a medida que aumenta el tamaño de cada sección del maniquí, la dosis se reduce, aproximadamente hasta el 72% y, cuando disminuye el tamaño de cada sección, mejora hasta en un 21% la calidad de la imagen debido a la reducción del ruido. Conclusiones: Se pudo observar que, a pesar de que las dosis para localización son bajas, la utilización de un simple escanograma, en la mayoría de los protocolos, no solo permite reducir la dosis suministrada al paciente, sino también efectuar menor cantidad de disparos en el equipo e incrementar la vida útil del tubo de rayos X, pues el aporte de un segundo escanograma no representa un impacto significativo en la calidad de imagen.

Abstract Given the increased use of computed tomography in the Costa Rican Social Security Fund during the last 10 years, it has become increasingly important to obtain images of the required diagnostic quality with the minimum radiation dose to the patient. To achieve this, computed tomography systems routinely use automatic exposure control, modulating the tube current according to the attenuation of the beam produced by the patient and obtained on scanogram. Aim: Check the operation of the automatic exposure control of a Canon Aquilion ONE scanner at the dose delivered to the patient and to verify the importance of performing a single or double scanogram for different clinical protocols. Methods : The behavior of the dose, the noise and the intensity of the current was analyzed in a phantom with different elliptical sections that vary their dimensions in the X-Y axes. The dose-length product was determined in different clinical protocols with the automatic exposure control activated due to a single or a double scanogram. Results: For fixed current intensities, as the size of each section of the phantom increases, the dose is reduced, approximately, up to 72% and when the size of each section decreases, the quality of image improves, due to noise reduction, up to 21%. Conclusions: It was observed that, despite the fact that the doses for localization are low, the use of a simple scanogram in most protocols not only reduces the dose to the patient, but also makes fewer shots in the equipment and increases the useful life of the X-ray tube, since the contribution of a second scanogram does not represent a significant impact on image quality.

Construction and optimization of automatic checking mode for unit dose dispensing system of oral drugs / 中国药房

OBJECTIVE To provide a reference for establishing an automatic checking mode and improving the checking efficiency of the unit dose dispensing system of oral drugs in hospital. METHODS The automatic checking process reengineering team was established in our hospital. ECRSI method was adopted to sort out the verification process and mode of drug bags for the unit dose formula of our hospital through five principles of eliminating， combining， rearranging， simplifying and increasing， and the hardware series problem and the problem of excessive system false-positive proportion were optimized. The drug bags for the unit dose formula were randomly selected from 10 wards， the efficiency and external error rates of manual check and automatic checking mode before and after optimization were compared， and the false-positive reporting failure in automatic checking mode was also compared before and after optimization. RESULTS After the establishment of the automatic checking mode of the unit dose formula for oral drugs， the average checking time of drug bags was significantly shorter than that of manual checking mode in the other 8 wards except for cardiovascular and renal departments （P＜0.05）. After the optimization of the automatic checking mode， the average checking time of drug bags in all wards was significantly shorter than that in manual checking mode （P＜0.05）. Compared with before optimization of the automatic checking mode， the average checking time of drug bags was shortened by 0.43 s， and the average checking time of drug bags in half of the wards was shortened significantly （P＜0.05）. At the same time， the false-positive proportion decreased from 96.83% before optimization to 92.76% after optimization （P＜0.05）. The external error rate dropped from 0.039‰ in manual checking mode to 0.019‰ before optimization and 0.015‰ after optimization （P＜0.05）. CONCLUSIONS Based on ECRSI method， the automatic checking mode for the unit dose dispensing system of oral drugs can effectively reduce the average checking time of drug bags， reduce external error and improve the work efficiency of pharmacists.

Design and development of a multifunctional moxibustion treatment machine based on heat-sensitive moxibustion therapy / 中国针灸

A multifunctional moxibustion treatment machine is designed and developed to assist the heat-sensitive moxibustion therapy. Through the motion control of the stepping motor by programmable logic controller (PLC), the automatic control is obtained for the acupoint detection of heat-sensitive moxibustion therapy and the manual operation of moxibustion. The skin temperature is monitored in real-time, using infrared non-contact temperature measurement technology. Based on the deviation of the temperature set value and the monitoring one, the distance between the moxibustion device and the exerted region is adjusted automatically by PLC so that the temperature is controlled practically. The multifunctional moxibustion treatment machine based on the heat-sensitive moxibustion therapy is capable of the operation control of mild moxibustion, circling moxibustion, sparrow-pecking moxibustion and along-meridian moxibustion techniques, as well as real-time monitoring of skin temperature. The temperature change curve of this machine is coincident with that obtained by the manual operation of heat-sensitive moxibustion. This multifunctional moxibustion treatment machine assists the delivery of heat-sensitive moxibustion therapy and it is satisfactory in temperature control and precise in operation.

Automatic sleep staging algorithm for stochastic depth residual networks based on transfer learning / 生物医学工程学杂志

The existing automatic sleep staging algorithms have the problems of too many model parameters and long training time, which in turn results in poor sleep staging efficiency. Using a single channel electroencephalogram (EEG) signal, this paper proposed an automatic sleep staging algorithm for stochastic depth residual networks based on transfer learning (TL-SDResNet). Firstly, a total of 30 single-channel (Fpz-Cz) EEG signals from 16 individuals were selected, and after preserving the effective sleep segments, the raw EEG signals were pre-processed using Butterworth filter and continuous wavelet transform to obtain two-dimensional images containing its time-frequency joint features as the input data for the staging model. Then, a ResNet50 pre-trained model trained on a publicly available dataset, the sleep database extension stored in European data format (Sleep-EDFx) was constructed, using a stochastic depth strategy and modifying the output layer to optimize the model structure. Finally, transfer learning was applied to the human sleep process throughout the night. The algorithm in this paper achieved a model staging accuracy of 87.95% after conducting several experiments. Experiments show that TL-SDResNet50 can accomplish fast training of a small amount of EEG data, and the overall effect is better than other staging algorithms and classical algorithms in recent years, which has certain practical value.

Application of automatic injection device based on automatic hemostasis in injection of radiopharmaceutical bolus injection / 生物医学工程学杂志

In clinical practice, radiopharmaceutical dynamic imaging technology requires the bolus injection method to complete injection. Due to the failure rate and radiation damage of manual injection, even experienced technicians still bear a lot of psychological burden. This study combined the advantages and disadvantages of various manual injection modes to develop the radiopharmaceutical bolus injector, and explored the application of automatic injection in the field of bolus injection from four aspects: radiation protection, occlusion response, sterility of injection process and effect of bolus injection. Compared with the current mainstream manual injection method, the bolus manufactured by the radiopharmaceutical bolus injector based on the automatic hemostasis method had a narrower full width at half maximum and better repeatability. At the same time, radiopharmaceutical bolus injector had reduced the radiation dose of the technician's palm by 98.8%, and ensured more efficient vein occlusion recognition performance and sterility of the entire injection process. The radiopharmaceutical bolus injector based on automatic hemostasis has application potential in improving the effect and repeatability of bolus injection.