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Exploring the assessment of post-cardiac valve surgery pulmonary complication risks through the integration of wearable continuous physiological and clinical data.

BMC medical informatics and decision making
BACKGROUND: Postoperative pulmonary complications (PPCs) following cardiac valvular surgery are characterized by high morbidity, mortality, and economic cost. This study leverages wearable technology and machine learning algorithms to preoperatively ...

A deep learning model for assistive decision-making during robot-aided rehabilitation therapies based on therapists' demonstrations.

Journal of neuroengineering and rehabilitation
BACKGROUND: A promising approach to improving motor recovery during rehabilitation is the use of robotic rehabilitation devices. These robotic devices provide tools to monitor the patient's recovery progress while providing highly standardized and in...

Design strategies for artificial intelligence based future learning centers in medical universities.

BMC medical education
BACKGROUND: This study explores the acceptance of artificial intelligence(AI) tools in medical students and its influencing factors, thus providing theoretical basis and practical guidance for the construction of future learning centers in medical un...

Optimizing hypoglycaemia prediction in type 1 diabetes with Ensemble Machine Learning modeling.

BMC medical informatics and decision making
BACKGROUND: Type 1 diabetes (T1D) is a chronic endocrine disorder characterized by high blood glucose levels, impacting millions of people globally. Its management requires intensive insulin therapy, frequent blood glucose monitoring, and lifestyle a...

Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches.

BMC medical informatics and decision making
BACKGROUND: The aim of this study was to evaluate the potential models to determine the most important anthropometric factors associated with type 2 diabetes mellitus (T2DM).

Automated strabismus detection and classification using deep learning analysis of facial images.

Scientific reports
Strabismus, or eye misalignment, is a common condition affecting individuals of all ages. Early detection and accurate classification are essential for proper treatment and avoiding long-term complications. This research presents a new deep-learning-...

Evaluating waist-to-hip ratio in youth using frequency-modulated continuous wave radar and machine learning.

Scientific reports
Waist-to-hip ratio (WHR) is an essential predictor of cardiometabolic diseases, but traditional tape-based WHR measurements in children and adolescents can cause discomfort due to direct contact and are prone to measurer variation. This study aimed t...

Using machine learning to predict outcomes following transcarotid artery revascularization.

Scientific reports
Transcarotid artery revascularization (TCAR) is a relatively new and technically challenging procedure that carries a non-negligible risk of complications. Risk prediction tools may help guide clinical decision-making but remain limited. We developed...

Machine Learning-Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study.

JMIR medical informatics
BACKGROUND: Chronic heart failure (CHF) is a serious threat to human health, with high morbidity and mortality rates, imposing a heavy burden on the health care system and society. With the abundance of medical data and the rapid development of machi...

Effect of Artificial Intelligence Helpfulness and Uncertainty on Cognitive Interactions with Pharmacists: Randomized Controlled Trial.

Journal of medical Internet research
BACKGROUND: Clinical decision support systems leveraging artificial intelligence (AI) are increasingly integrated into health care practices, including pharmacy medication verification. Communicating uncertainty in an AI prediction is viewed as an im...