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Establishment of a postoperative delirium risk prediction model for elderly hip fracture patients based on machine learning algorithms.

BMC geriatrics
BACKGROUND: Although no definitive treatment exists, 30-40% of postoperative delirium cases are preventable through early risk identification and intervention. Therefore our aim was to develop and evaluate a postoperative delirium risk prediction mod...

A baseline study of interpretable machine learning using GC-MS breath VOCs for classifying asthma, bronchiectasis, and COPD.

Scientific reports
Accurate differentiation among asthma, bronchiectasis, and chronic obstructive pulmonary disease (COPD) remains a critical challenge due to overlapping clinical symptoms and limitations of conventional diagnostic tools. This study establishes a trans...

Evaluating Multiple Input Strategies of Large Language Models for Gallbladder Polyps on Ultrasound: Comparative Study.

JMIR medical informatics
BACKGROUND: Gallbladder polyps have a high prevalence and are predominantly benign lesions, often detected via ultrasound. They impose diagnostic burdens on radiologists while generating substantial patient demand for report interpretation. Benign po...

Adherence to Accelerometer Use in Older Adults Undergoing mHealth Cardiac Rehabilitation: Secondary Analysis of a Randomized Clinical Trial.

Journal of medical Internet research
BACKGROUND: Wearable accelerometers, which continuously record physical activity metrics, are commonly used in mobile health-enabled cardiac rehabilitation (mHealth-CR). The association between adherence to accelerometer use during mHealth-CR and imp...

Using AI-Based Virtual Simulated Patients for Training in Psychopathological Interviewing: Cross-Sectional Observational Study.

JMIR medical education
BACKGROUND: Virtual simulated patients (VSPs) powered by generative artificial intelligence (GAI) offer a promising tool for training clinical interviewing skills; yet, little is known about how different system- and user-level variables shape studen...

Predictive modeling of hematoma expansion from non-contrast computed tomography in spontaneous intracerebral hemorrhage patients.

eLife
Hematoma expansion is a consistent predictor of poor neurological outcome and mortality after spontaneous intracerebral hemorrhage (ICH). An incomplete understanding of its biophysiology has limited early preventative intervention. Transport-based mo...

Comparative analysis of retinal and cerebral vascular responses to CO₂ using Doppler optical coherence tomography and transcranial Doppler ultrasound.

Physics in medicine and biology
Access to blood flow data in cerebral and retinal vascular beds is crucial for diagnosing cerebrovascular diseases. This study addresses two technological gaps: (1) simultaneous recording of vascular responses in the brain and eye by integrating tran...

Construction of an intelligent screening model for allergic rhinitis based on routine blood tests.

PloS one
The incidence of allergic rhinitis (AR) has been increasing annually, severely impacting patients' quality of life and increasing socioeconomic burdens. The limitations of current diagnostic methods have made the development of efficient, low-cost ea...

Enhancing mathematical modeling competencies through AI-powered VR.

PloS one
BACKGROUND: Improving students' problem-solving skills is one of the primary objectives of mathematics education. Problem-solving skills are closely related to the mathematical modeling process and the competencies required in this process, which are...

Reliability, validity, and correlates of an AI voice emotion recognition app among nurses.

PloS one
BACKGROUND: Digital tools are increasingly widespread in healthcare, particularly in the fields of emotion recognition and mental health assessment.