AI Medical Compendium

Optimizing acquisition time and injected dose in 18F-FDG PET/CT imaging using deep learning: enhancing image protocol efficiency and safety.

BMC medical informatics and decision making Jun 5, 2026

BACKGROUND: This study aims to evaluate the effectiveness of deep learning algorithms in simulating standard acquisition time images from shortened acquisition times in 18F-FDG PET/CT imaging, thereby optimizing both image quality and radiopharmaceut... read more

Large Language Models in Healthcare Simulation Education: A Bibliometric Analysis with AI-Assisted Screening

medRxiv Jun 4, 2026

Large language models (LLMs) such as ChatGPT are rapidly reshaping healthcare education and simulation-based training in non-technical skills (NTS), yet no bibliometric analysis has mapped this landscape. We searched seven open-access databases (Open... read more

urology

Precision Imaging to Evaluate Kaposi Sarcoma (PRIME-KS): protocol for a multicountry novel artificial intelligence-based imaging device

medRxiv Jun 4, 2026

Abstract Background: Kaposi sarcoma (KS) is the most common cancer among men in several Eastern African countries, yet treatment monitoring relies on imprecise, time-consuming ruler-based measurements defined by the AIDS Clinical Trial Group (ACTG). ... read more

oncology

Prediction of delirium in trauma patients using interpretable machine learning.

Scientific reports Jun 5, 2026

This study aimed to identify key risk factors for delirium in trauma patients and to develop an interpretable machine learning model using routinely available demographic, clinical, and laboratory data collected at initial trauma center presentation.... read more

Non-invasive periodontal screening using self-reported-oral-health (SROH) questionnaire and salivary biomarkers: development and validation of machine learning models.

BMC oral health Jun 5, 2026

BACKGROUND: Accurate and accessible screening tools for periodontitis are essential for early detection and disease prevention. This study evaluated a non-invasive diagnostic approach integrating sociodemographic data, self-reported oral health (SROH... read more

Physics-informed neural network-based simulation of pulmonary arterial hemodynamics abnormalities.

Biomedizinische Technik. Biomedical engineering Jun 5, 2026

OBJECTIVES: To predict abnormal pulmonary artery hemodynamics caused by ventricular septal defect (VSD) using Physics-Informed Neural Networks (PINN) and address the challenges of high computational cost in traditional Computational Fluid Dynamics (C... read more

Development, validation, and user-centric evaluation of an interpretable machine learning decision support tool for the preoperative prediction of mild bleeding disorders (MBD-Check): a prospective diagnostic prediction study.

The Lancet. Digital health Jun 4, 2026

BACKGROUND: Mild bleeding disorders are the most common inherited bleeding disorders, often leading to perioperative haemorrhages. Preoperative screening for mild bleeding disorders remains challenging due to the limitations of existing screening too... read more

How Following Medical Artificial Intelligence Advice Can Mitigate Malpractice Liability: Cross-National Insights from a Randomized Trial.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine Jun 4, 2026

Artificial intelligence (AI) increasingly influences clinical decision-making, yet its recommendations may diverge from standard care. Although malpractice concerns are thought to discourage physicians from following AI advice, experimental evidence ... read more

AI-based oculomics for trajectory-driven risk stratification of pathologic myopia in paediatric high myopia.

The British journal of ophthalmology Jun 4, 2026

AIMS: To identify early oculomic biomarkers predictive of pathologic myopia (PM) in children with high myopia (HM) and to develop an artificial intelligence (AI)-based model for individualised risk stratification. METHODS: This prospective longitudin... read more

Machine learning (ML) in intraoperative neuromonitoring (IONM): proof of concept.

Spine deformity Jun 4, 2026

PURPOSE: Intraoperative neuromonitoring (IONM) improves safety during pediatric spinal deformity surgery by providing real-time neurophysiological assessment, enabling the earlier detection of neural compromise and the potential prevention of permane... read more

Artificial Intelligence Medical Compendium