Latest AI and machine learning research in product alert for healthcare professionals.
The Expected Pass Turnovers (xPT) model advances turnover probability quantification in professional football, but the inclusion of post-pass descriptive features such as ball speed and distance moved introduces temporal leakage and limits real-time tactical utility. This study compares the original xPT framework with leakage-corrected alternatives across four modeling approaches: mixed-effects lo...
Cancer patients are particularly susceptible to Drug-Drug Interactions (DDIs) due to frequent polypharmacy in oncology care. Co-administered drugs can increase toxicity or reduce effectiveness, potentially causing serious adverse events-for example, QTc-prolonging Tyrosine Kinase Inhibitors with CYP3A4 inhibitors can lead to torsade de pointes. Traditional DDI identification methods are time-consu...
Predicting drug-induced cardiotoxicity remains one of the most important challenges in drug safety, contributing to a substantial share of clinical tr...
PURPOSE: To evaluate whether an artificial intelligence (AI)-assisted surveillance device, AUGi, improves documentation of falls and injury rates in a...
PURPOSE: To develop and validate machine learning models to predict post-tonsillectomy hemorrhage. METHODS: This was a machine learning analysis of a ...
Organ transplantation remains a gold-standard intervention for numerous end-stage organ failure diseases. However, allograft rejection is still a barr...
PURPOSE: To evaluate the accuracy of automatic surface tracking registration with a smartphone augmented reality (AR) guidance system for percutaneous...
Radial artery puncture, a routine arterial cannulation procedure for perioperative and critical care settings, is limited by high first-attempt failur...
Patent foramen ovale (PFO) has been increasingly associated with otherwise unexplained syncope, but predictors of syncope recurrence after percutaneou...
BACKGROUND: Artificial intelligence (AI)-enabled "ambient" documentation may reduce clinician administrative burdens and improve care delivery, but im...
STUDY OBJECTIVE: To compare the quality of AI-generated responses to gynecologic post-operative questions with educational materials published by prof...
BackgroundPost-stroke cognitive impairment (PSCI) is a major vascular contributor to dementia, significantly impacting long-term recovery and quality ...
Accurate estimation of the Post-Mortem Interval (PMI) and Post-Mortem Submersion Interval (PMSI) remains a persistent challenge in forensic science, e...
Cancer therapeutics account for a significant proportion of new drug development, reflecting advances in diagnosis, treatment, and disease control. Ho...
BACKGROUND: Large language models (LLMs) are rapidly incorporated into medical education and examination preparation; yet, most benchmarking evidence ...
BACKGROUND: Over the past century, medical education has undergone a profound transformation, evolving from unregulated apprenticeships into a highly ...
Artificial intelligence is expanding rapidly in cardiovascular medicine, but its value in internal medicine depends less on raw model performance than...
The health informatics field's pursuit of personalized healthcare continuously faces constraints from patients, clinicians, and resource limitations. ...
Healthcare IoT systems increasingly rely on interconnected, resource-constrained devices that are vulnerable to both classical and emerging quantum-en...
BACKGROUND: Diabetic retinopathy (DR), a microvascular complication of diabetes, is an important cause of preventable blindness and can cause a signif...