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Sex-specific machine learning models for carotid plaque prediction in individuals with fatty liver disease: a cross-sectional study.

BMJ open
INTRODUCTION: Early detection of carotid plaque prevents stroke and myocardial infarction. Individuals with fatty liver might be at an increased risk of developing carotid plaque, yet limited access to carotid artery ultrasound underscores the need f...

Utilization of AI Among Medical Students and Development of AI Education Platforms in Medical Institutions: Cross-Sectional Study.

JMIR human factors
BACKGROUND: The emergence of artificial intelligence (AI) is driving digital transformation and reshaping medical education in China. Numerous medical schools and institutions are actively implementing AI tools for case-based learning, literature ana...

Developing an AI-Assisted Tool That Identifies Patients With Multimorbidity and Complex Polypharmacy to Improve the Process of Medication Reviews: Qualitative Interview and Focus Group Study.

Journal of medical Internet research
BACKGROUND: Structured medication reviews (SMRs) are an essential component of medication optimization, especially for patients with multimorbidity and polypharmacy. However, the process remains challenging due to the complexities of patient data, ti...

Assessment of Blood Glucose Measurement Using New Noninvasive Technology: Protocol and Methodology.

JMIR research protocols
BACKGROUND: Diabetes mellitus (DM) is a major noncommunicable disease with a significant increase in prevalence, especially in low- and middle-income countries. The latest International Diabetes Federation Diabetes Atlas (2025) reports that 11.1% of ...

Linking Patient-Reported and Clinician-Assessed Wound Status via Chatbot-Based Digital Surveillance for Wound Infection: Retrospective Observational Study.

JMIR formative research
BACKGROUND: Digital wound monitoring has become increasingly feasible with the widespread use of smartphones and mobile messaging platforms. Although most previous studies have focused on chronic wounds and demonstrated the clinical benefits of remot...

Long-term benefit from high-dose ifosfamide in sarcoma depends on sustained prior control and timely intervention: a machine learning analysis.

Journal of cancer research and clinical oncology
PURPOSE: High-dose ifosfamide (HD-IFO) remains an effective regimen for advanced bone and soft tissue sarcomas, but predictors of long-term benefit are poorly defined. This study evaluated clinical outcomes and prognostic factors using machine learni...

AI-MDT: an automatic and intelligent multidisciplinary team consultations platform for lung cancer diagnosis.

Journal of cancer research and clinical oncology
PURPOSE: Multidisciplinary team (MDT) consultations are crucial for managing pulmonary nodules, yet face challenges in efficiency, evidence-based decision support, and data utilization within the MDT process. We present an integrated artificial intel...

A pretrained foundation model for headache disorders based on magnetoencephalography.

Journal of neural engineering
Foundation models have demonstrated transformative potential in medical artificial intelligence but remain underexplored in functional neuroimaging, particularly magnetoencephalography (MEG). This study aims to develop a domain-specific, self-supervi...

Hypoxemia prediction in pediatric patients under general anesthesia using machine learning: A retrospective observational study and external validation.

PloS one
BACKGROUND: Pediatric patients under general anesthesia are particularly vulnerable to hypoxemia, which can lead to rapid oxygen desaturation. This vulnerability necessitates heightened vigilance from anesthesiologists, making pediatric anesthesia ma...

Understanding the influence of design-related factors on human-AI teaming in a face matching task.

Cognitive research: principles and implications
There has been a steep rise in the use of decision aids enabled by artificial intelligence (AI) for facial identity verification. The use of such systems and the impact of their implementation on human decision-making is still not well understood. Th...