Heavy Studying Algorithms Properly Move Brassica rapa Varieties Using Electronic digital Photographs

09±10.1 (range, 43 to 76) min and the median cardiopulmonary bypass time was 90.1±11.9 (range, 66 to 114) min. No hospital mortality was observed. In the postoperative period, two patients experienced renal insufficiency. Hemofiltration was initiated in these patients and no dialysis was required at two weeks. One patient had postoperative atrial fibrillation and one patient had pericardial effusion leading to cardiac tamponade and this patient underwent reoperation. The patients were followed up for a mean of four years and control echocardiography didn"t detect increase in mitral regurgitation degree. Conclusion Transaortic edge-to-edge mitral valve repair can be used in high-risk patients undergoing aortic valve replacement. This technique is feasible with shorter cross-clamp time and can reduce mortality and morbidity in selected high-risk patients. Copyright © 2019, Turkish League Against Rheumatism.Background This study aims to investigate the effect of time interval between coronary angiography and coronary artery bypass grafting surgery on postoperative acute kidney injury in patients with diabetes mellitus. Methods Between December 2013 and November 2016, a total of 421 diabetic patients (274 males, 147 females; mean age 60±9.2 years; range, 31 to 84 years) who underwent coronary artery bypass grafting were included in the study. Data including demographic characteristics of the patients, comorbidities, medical, and surgical histories, previous coronary angiographies, and operative and laboratory results were retrospectively analyzed. The patients were divided into two groups as those with acute kidney injury (n=108) and those without acute kidney injury (n=313). The Risk, Injury, Failure, Loss, End-Stage Kidney Disease (RIFLE) criteria were used to define acute kidney injury. The patients were further classified into three subgroups according to the time interval 0-3 days, 4-7 days, and >7 days. Results There was no statistically significant difference in the median time between coronary angiography and coronary artery bypass grafting between the patients with and without acute kidney injury (11.5 and 12.0 days; respectively p=0.871). There was no significant difference in the risk factors for acute kidney injury among the subgroups. Multivariate analysis revealed that previous myocardial infarction (odds ratio [OR] 5.192, 95% confidence interval [CI] 2.176-12.38; p less then 0.001) and the increase in the creatinine levels in the first postoperative day (OR 4.102 and 95% CI 1.278- 13.17; p=0.018) were independent predictors of acute kidney injury. Conclusion Coronary artery bypass grafting can be performed without any delay after coronary angiography without an increase in the postoperative risk of acute kidney injury in patients with diabetes mellitus. Copyright © 2019, Turkish League Against Rheumatism.Objectives We investigated associations between full Electronic Medical Record (EMR) system adoption and drug use in healthcare organizations (HCOs) to explore whether EMR system features such as electronic prescribing, medicines reconciliation, and decision support, might be related to drug use by using the relevant nation-wide data. Methods The study design was cross-sectional. Survey data of the level of adoption of EMR systems were collected for the Organization for Economic Co-operation and Development benchmarking information and communication technologies (ICT) study between November 2013 and January 2014, in Korea. Survey respondents were hospital chief information officers and medical practitioners in primary care clinics. From the national health insurance administrative dataset, two outcomes, the rate of antibiotic prescription and polypharmacy with ≥6 drugs, were extracted. Results We found that full EMR adoption showed a 16.1% lower antibiotic drug prescription than partial adoption including paper-based medical charts in the hospital only (p = 0.041). Between EMR adoption status and polypharmacy prescription, only those clinics which fully adopted EMR showed significant associations with higher polypharmacy prescriptions (36.9%, p = 0.001). Conclusions The findings suggested that there might be some confounding effects present and sophisticated ICT may provide some benefits to the quality of care even with some mixed results. Although a negative relationship between full EMR system adoption and antibiotic drug use was only significant in hospitals, EMR system functions searching drugs or listing specific patients might facilitate antibiotic drug use reduction. Positive relationships between full EMR system adoption and polypharmacy rate in general hospitals and clinics, but not hospitals, require further research. © 2020 The Korean Society of Medical Informatics.Objectives Back pain, especially lower back pain, is experienced in 60% to 80% of adults at some points during their lives. Various studies have found that lower back pain is a very common problem among adolescents, and the highest incidence rates are for adults in their 30s. There has been a remarkable increase in using computer-aided diagnosis to assist doctors in the interpretation of medical images. Spine segmentation in computed tomography (CT) scans using algorithmic methods allows improved diagnosis of back pain. Methods In this study, we developed a web-based automatic spine segmentation method using deep learning and obtained the dice coefficient by comparison with the predicted image. Our method is based on convolutional neural networks for segmentation. More specifically, we train a hierarchical data format file using U-Net architecture and then insert the test data label to perform segmentation. Thus, we obtained more specific and detailed results. A total of 344 CT images were used in the experiment. Of these, 330 were used for learning, and the remaining 14 for testing. Selleckchem Olaparib Results Our method achieved an average dice coefficient of 90.4%, a precision of 96.81%, and an F1-score of 91.64%. Conclusions The proposed web-based deep learning approach can be very practical and accurate for spine segmentation as a diagnostic method. © 2020 The Korean Society of Medical Informatics.