AIMC Topic: Female

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Performance of a Deep Learning Diabetic Retinopathy Algorithm in India.

JAMA network open
IMPORTANCE: While prospective studies have investigated the accuracy of artificial intelligence (AI) for detection of diabetic retinopathy (DR) and diabetic macular edema (DME), to date, little published data exist on the clinical performance of thes...

Ethics in Patient Preferences for Artificial Intelligence-Drafted Responses to Electronic Messages.

JAMA network open
IMPORTANCE: The rise of patient messages sent to clinicians via a patient portal has directly led to physician burnout and dissatisfaction, prompting uptake of artificial intelligence (AI) to alleviate this burden. It is important to understand patie...

Machine Learning-Based Prediction of Early Complications Following Surgery for Intestinal Obstruction: Multicenter Retrospective Study.

Journal of medical Internet research
BACKGROUND: Early complications increase in-hospital stay and mortality after intestinal obstruction surgery. It is important to identify the risk of postoperative early complications for patients with intestinal obstruction at a sufficiently early s...

Virtual Patient Simulations Using Social Robotics Combined With Large Language Models for Clinical Reasoning Training in Medical Education: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: Virtual patients (VPs) are computer-based simulations of clinical scenarios used in health professions education to address various learning outcomes, including clinical reasoning (CR). CR is a crucial skill for health care practitioners,...

Detecting Artificial Intelligence-Generated Versus Human-Written Medical Student Essays: Semirandomized Controlled Study.

JMIR medical education
BACKGROUND: Large language models, exemplified by ChatGPT, have reached a level of sophistication that makes distinguishing between human- and artificial intelligence (AI)-generated texts increasingly challenging. This has raised concerns in academia...

Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study.

JMIR aging
BACKGROUND: Depression, characterized by persistent sadness and loss of interest in daily activities, greatly reduces quality of life. Early detection is vital for effective treatment and intervention. While many studies use wearable devices to class...

Applying machine learning to high-dimensional proteomics datasets for the identification of Alzheimer's disease biomarkers.

Fluids and barriers of the CNS
PURPOSE: This study explores the application of machine learning to high-dimensional proteomics datasets for identifying Alzheimer's disease (AD) biomarkers. AD, a neurodegenerative disorder affecting millions worldwide, necessitates early and accura...

Machine learning for the rElapse risk eValuation in acute biliary pancreatitis: The deep learning MINERVA study protocol.

World journal of emergency surgery : WJES
BACKGROUND: Mild acute biliary pancreatitis (MABP) presents significant clinical and economic challenges due to its potential for relapse. Current guidelines advocate for early cholecystectomy (EC) during the same hospital admission to prevent recurr...

Leveraging machine learning for duration of surgery prediction in knee and hip arthroplasty - a development and validation study.

BMC medical informatics and decision making
BACKGROUND: Duration of surgery (DOS) varies substantially for patients with hip and knee arthroplasty (HA/KA) and is a major risk factor for adverse events. We therefore aimed (1) to identify whether machine learning can predict DOS in HA/KA patient...

An interpretable machine learning model with demographic variables and dietary patterns for ASCVD identification: from U.S. NHANES 1999-2018.

BMC medical informatics and decision making
Current research on the association between demographic variables and dietary patterns with atherosclerotic cardiovascular disease (ASCVD) is limited in breadth and depth. This study aimed to construct a machine learning (ML) algorithm that can accur...