Artificial Intelligence Medical Compendium

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

Showing 58,211 to 58,220 of 227,634 articles

End-to-end deep learning versus machine learning for biomarker discovery in cancer genomes

bioRxiv Jan 26, 2026
Background: Accurate determination of genomic biomarkers from tumor sequencing is fundamental to precision oncology, informing disease classification and treatment decisions. In practice, biomarker inference relies on computational pipelines that oft... read more 
bioinformatics

Behavioral Assessment Reliability in Clinical Phenotyping and Biomarker Research for Autism

medRxiv Jan 26, 2026
Autism Spectrum Disorder standardized behavioral assessments provide quantitative measures of symptoms, yet their reliability and consistency have not been systematically evaluated. We present the first large-scale comparative analysis of four widely... read more 
psychiatry and clinical psychology

C-RLM: Schema-Enforced Recursive Synthesis for Auditable, Long-Context Clinical Documentation

medRxiv Jan 26, 2026
Clinical decision-making for multi-morbid patients requires synthesizing evidence from lengthy, fragmented records-a task that exposes the limitations of standard Retrieval-Augmented Generation (RAG) and long-context Large Language Models (LLMs), whi... read more 
health informatics

Automated Echocardiographic Detection of Congenital Heart Disease Using Artificial Intelligence

medRxiv Jan 26, 2026
Background: Delayed or missed diagnosis of congenital heart disease (CHD) contributes to excess pediatric mortality worldwide. Echocardiography (echo) is central to diagnosing and triaging CHD, yet expert interpretation remains a scarce and maldistri... read more 
cardiovascular medicine

Early Dementia Diagnosis in Older Adults through Machine Learning: A Cross-Sectional fMRI Data Analysis

medRxiv Jan 26, 2026
Background: Early diagnosis of dementia can significantly improve care planning and patient outcomes while delaying progression. Machine learning algorithms can identify patterns in clinical and neuroimaging data that may aid in the early detection o... read more 
health informatics

A Clinical Theory-Driven Deep Learning Model for Interpretable Autism Severity Prediction

medRxiv Jan 26, 2026
Autism spectrum disorder (ASD) affects a substantial proportion of children worldwide, yet clinical assessment of symptom severity remains resource-intensive and unevenly accessible. Artificial intelligence (AI) has transformative potential to suppor... read more 
health informatics

A Machine Learning Analysis of The Bead Maze Hand Function Test for Predicting Manual Dexterity in Children.

medRxiv Jan 26, 2026
Comprehending how forces are applied to an object during manipulation can help provide important insights into the quality of behavior in daily tasks. We have developed the Bead Maze Hand Function test to objectively measure the quality of hand funct... read more 
pediatrics

Multimodal Fusion of Pathology Free-Text and Clinical Data Enhances Complication-Risk Discrimination After Implant-Based Breast Reconstruction

medRxiv Jan 25, 2026
Implant-based breast reconstruction is the most common surgical option following mastectomy for breast cancer. Despite its prevalence, up to one-third of patients develop complications within two years. Existing machine-learning models for predicting... read more 
health informatics

Prognostic Risk Refinement using Artificial Intelligence in HR+/HER2- Early Breast Cancer: Implications for CDK4/6 Eligibility Criteria

medRxiv Jan 25, 2026
Patient selection and enrolment into phase III randomized clinical trials (RCTs) of adjuvant cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitor therapies depend on accurate risk definition. However, standard clinicopathologic criteria incompletely ca... read more 
oncology

Comparative Performance of agentic AI and Physicians in Taking Clinical History across Leading Large Language Models (LLMs)

medRxiv Jan 25, 2026
Comprehensive clinical history taking is essential for high-quality care. We hypothesized that large language models (LLMs), guided by a structured agentic framework, can efficiently obtain clinically meaningful patient histories. We developed an ite... read more 
health informatics
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