Artificial Intelligence Medical Compendium

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

Showing 25,151 to 25,160 of 217,472 articles

Learning dynamics of unsupervised deep learning reveal epoch-specific genetic architectures of brain morphology

bioRxiv Apr 28, 2026
Representation learning is an emerging paradigm for deriving phenotypes from complex measurements (e.g., imaging) for genetic discovery. However, the learning dynamics of deep neural networks, especially the evolution of representations during traini... read more 
bioinformatics

Improving Biological Sequence Prediction with AlphaFold2 Representation

bioRxiv Apr 28, 2026
Motivation: Accurate prediction of functional sites from primary sequences is essential for elucidating biological mechanisms and advancing rational drug design. However, traditional sequence-based features areinherently unable to capture complex str... read more 
bioinformatics

Protein Function Prediction with Pretrained ProtT5 Embeddings and Gradient Boosting

bioRxiv Apr 28, 2026
Protein function prediction remains a central challenge in computational biology due to the extreme sparsity and long-tail distribution of Gene Ontology (GO) [1] annotations. Advances in protein language models enable the extraction of dense, fixed-l... read more 
bioinformatics

Interpretable Transformer-Based Phase Recognition for Transabdominal Preperitoneal Laparoscopic Inguinal Hernia Repair

medRxiv Apr 28, 2026
Background: Surgical phase recognition is a critical prerequisite for context-aware operating rooms and automated skill assessment. While artificial intelligence (AI) benchmarking has progressed for simpler procedures, applying surgical phase recogni... read more 
medical education

Validation of an AI-Assisted Framework for Systematic Bias Assessment in Observational Studies

medRxiv Apr 28, 2026
Background: The rapid expansion of medical literature has led to substantial variability and frequent contradictions in study findings, making it increasingly difficult to distinguish meaningful signals from noise. Much of this variability arises fro... read more 
epidemiology

One Size Fits All? Comparing Foundation and Task-specific Models for Retinal Fluid Segmentation

medRxiv Apr 28, 2026
Retinal fluids, detectable through optical coherence tomography (OCT), are key biomarkers for retinal diseases such as diabetic macular edema and age-related macular degeneration, guiding treatment decisions and monitoring response to therapy. Automa... read more 
health informatics

From simulation to pedagogy: structured AI standardized patients for clinical communication training validated through multi-model and randomized evaluation

medRxiv Apr 28, 2026
Standardized patients (SPs) are central to clinical communication training but are constrained by cost, scalability, and reliance on trained actors. We present AI standardized patients (AI-SPs), large language model-driven simulators governed by a th... read more 
medical education

Silent numerical failures in large language model-generated pharmacokinetic simulation code: a benchmark against target-controlled infusion validation criteria using the Marsh propofol model

medRxiv Apr 28, 2026
Background. Large language models (LLMs) are increasingly used by clinicians to generate executable code for pharmacokinetic (PK) simulation. Whether such code meets the accuracy standards of target-controlled infusion systems has not been systematic... read more 
health informatics

Development and validation of a lesion-supervised deep learning system for diabetic retinopathy grading according to UK national screening criteria

medRxiv Apr 28, 2026
Background: Diabetic retinopathy (DR) is the leading cause of preventable blindness among working-age adults worldwide, yet screening coverage remains inadequate, particularly in low- and middle-income countries. Automated deep learning systems offer... read more 
health informatics

Detection of bronchopulmonary dysplasia in infants and prediction of school-age lung function from tidal breathing data using recurrent neural networks

medRxiv Apr 28, 2026
Objective: To test whether machine learning (ML) models trained on tidal breathing flow time series can discriminate between individuals with and without respiratory disease and predict lung function indices obtained from conventional pulmonary funct... read more 
respiratory medicine
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