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Grading of diabetic retinopathy using a pre-segmenting deep learning classification model: Validation of an automated algorithm.
Acta ophthalmologica
Oct 19, 2024
PURPOSE: To validate the performance of autonomous diabetic retinopathy (DR) grading by comparing a human grader and a self-developed deep-learning (DL) algorithm with gold-standard evaluation.
External evaluation of a commercial artificial intelligence-augmented digital auscultation platform in valvular heart disease detection using echocardiography as reference standard.
International journal of cardiology
Oct 19, 2024
OBJECTIVE: There are few studies evaluating the accuracy of commercially available AI-powered digital auscultation platforms in detecting valvular heart disease (VHD). Therefore, the utility of these systems for diagnosing clinically significant VHD ...
Development of a machine learning model for precision prognosis of rapid kidney function decline in people with diabetes and chronic kidney disease.
Diabetes research and clinical practice
Oct 19, 2024
AIMS: To develop a machine learning model for predicting rapid kidney function decline in people with type 2 diabetes (T2D) and chronic kidney disease (CKD) and to pinpoint key modifiable risk factors for targeted interventions.
Preoperative identification of early extrahepatic recurrence after hepatectomy for colorectal liver metastases: A machine learning approach.
World journal of surgery
Oct 19, 2024
BACKGROUND: Machine learning (ML) may provide novel insights into data patterns and improve model prediction accuracy. The current study sought to develop and validate an ML model to predict early extra-hepatic recurrence (EEHR) among patients underg...
Development and Validation of an Artificial Intelligence-Assisted Patient Education Material for Ostomy Patients: A Methodological Study.
Journal of advanced nursing
Oct 18, 2024
AIM: To develop and test the validity of an artificial intelligence-assisted patient education material for ostomy patients.
Assessment of machine learning classifiers for predicting intraoperative blood transfusion in non-cardiac surgery.
Transfusion clinique et biologique : journal de la Societe francaise de transfusion sanguine
Oct 18, 2024
BACKGROUND: This study aimed to develop a machine learning classifier for predicting intraoperative blood transfusion in non-cardiac surgeries.
Machine learning-based CT radiomics approach for predicting occult peritoneal metastasis in advanced gastric cancer preoperatively.
Clinical radiology
Oct 18, 2024
AIM: To develop a machine learning-based CT radiomics model to preoperatively diagnose occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC) patients.
The Efficacy of a Food Supplement in the Treatment of Tinnitus with Comorbid Headache: A Statistical and Machine Learning Analysis with a Literature Review.
Audiology & neuro-otology
Oct 18, 2024
INTRODUCTION: Tinnitus, the perception of sound without an external auditory stimulus, affects approximately 10-15% of the population and is often associated with significant comorbidities such as headaches. These conditions can severely impact the q...
Impact of a clinical pharmacist-led, artificial intelligence-supported medication adherence program on medication adherence performance, chronic disease control measures, and cost savings.
Journal of the American Pharmacists Association : JAPhA
Oct 18, 2024
BACKGROUND: Chronic diseases are the leading cause of disability and death in the United States. Clinical pharmacists have been shown to optimize health outcomes and reduce health care expenditures in patients with chronic diseases through improving ...
Diagnostic performance of single-lead electrocardiograms for arterial hypertension diagnosis: a machine learning approach.
Journal of human hypertension
Oct 18, 2024
Awareness and early identification of hypertension is crucial in reducing the burden of cardiovascular disease (CVD). Artificial intelligence-based analysis of 12-lead electrocardiograms (ECGs) can already detect arrhythmias and hypertension. We perf...
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