Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 39,171 to 39,180 of 223,737 articles

HCLmNet: A unified hybrid continual learning strategy multimodal network for lung cancer survival prediction.

PloS one
Lung cancer survival prediction remains one of the most challenging tasks in modern healthcare, as accurate and adaptive prediction models are essential for improving patient outcomes. However, the continuous inflow of new patient data in hospital en... read more 

Using Natural Language Prompts With AI Models for Low-Cost Assistive Software Design: Exploratory Comparative Evaluation.

JMIR rehabilitation and assistive technologies
BACKGROUND: This study investigates the capacity of 7 artificial intelligence (AI) models, 5 free and 2 paid, to generate functional software for designing low-cost, personalized assistive products. OBJECTIVE: The objective was to determine which mod... read more 

Comparison of Large Language Models with Rules-Based Natural Language Processing Algorithms for Extracting Data from Operative Notes.

The Journal of bone and joint surgery. American volume
BACKGROUND: We aimed to develop automated data extraction pipelines with large language models (LLMs) to extract registry data from total hip arthroplasty (THA) operative notes and compare the performance with that of existing natural language proces... read more 

MRI-Based Synthetic CT Shows Promise as a Radiation-Free Alternative to Conventional CT in Orthopaedics.

The Journal of bone and joint surgery. American volume
➢ Computed tomography (CT) remains the gold standard for bone imaging, but radiation risks, especially in children, are driving interest in alternatives.➢ Magnetic resonance imaging (MRI)-based techniques are emerging as a radiation-free alternative ... read more 

A Bilingual Arabic-English Ambient AI Scribe for Clinical Documentation: Prospective Evaluation Study.

JMIR medical informatics
BACKGROUND: Medical ambient artificial intelligence (AI) scribes reduce documentation burden, but the current evidence is almost entirely from English systems. In the Arabic-speaking world, physicians converse mainly in Arabic and write clinical note... read more 

Thrombopoietin receptor agonists in immune thrombocytopenia: a comparative review of mechanisms, efficacy, and the future of personalized management.

Expert opinion on pharmacotherapy
INTRODUCTION: Thrombopoietin receptor agonists (TPO-RAs) have reshaped the management of chronic immune thrombocytopenia (ITP) by directly targeting impaired platelet production, a mechanism previously overshadowed by immune-mediated destruction. The... read more 

Longitudinal and Multimodal Recording System to Capture Real-World Patient-Clinician Conversations for AI and Encounter Research: Protocol for an Observational Study.

JMIR research protocols
BACKGROUND: The promise of artificial intelligence (AI) in medicine depends on its ability to learn from data that reflect what matters to patients and clinicians in the care process. Most existing models are trained on electronic health records (EHR... read more 

Unsupervised Phenomapping of Perioperative Risk in Stable Coronary Artery Disease: Revealing Limitations of the Revised Cardiac Risk Index.

European journal of preventive cardiology
AIMS: To derive unsupervised clinical phenotypes in patients with stable coronary artery disease (CAD) undergoing elective non-cardiac surgery and evaluate phenotype-stratified performance of the Revised Cardiac Risk Index (RCRI) and laboratory-augme... read more 

Automatic Multi-Class Classification of 3D Relationships Between the Mandibular Third Molar and Canal on CBCT Using a Geometry-Aware Network.

Dento maxillo facial radiology
OBJECTIVES: Accurate three-dimensional (3D) evaluation of the spatial relationship between the mandibular third molar (M3) and the mandibular canal (MC) is critical for assessing the risk of nerve injury during M3 extraction. The purpose of this stud... read more 

Graph-Based Classification with GNN-Explainer for Predicting Cardiac Toxicity Associated with Multi-Ion Channel Blockers.

Chemical research in toxicology
Cardiotoxicity remains a critical concern in drug development, often leading to late-stage attrition of promising compounds. While traditional assessments focus on Kv11.1 channel inhibition, the Comprehensive in Vitro Proarrhythmic Assay (CiPA) initi... read more