Artificial Intelligence Medical Compendium

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

Showing 1 to 10 of 215,899 articles

Endpoint-aligned artificial intelligence for biopsy-sparing assessment of suspected basal cell carcinoma

medRxiv Jul 31, 2026
Basal cell carcinoma (BCC) care follows a sequence of decisions from triage to pathological subtyping and depth assessment, and the information available changes at each step. To date, no artificial-intelligence (AI) tool using non-invasive inputs ha... read more 
dermatology

A Neuro-Symbolic Knowledge Graph and Large Language Model Hybrid Architecture for Multi-Modality Mental Health Counseling

medRxiv Jul 31, 2026
Background: Depression and anxiety are managed largely between clinical visits, yet outpatient care lacks scalable, accountable mechanisms for between-visit support. Large language models converse fluently but fuse clinical reasoning with language ge... read more 
psychiatry and clinical psychology

Population genomics of four-dimensional cardiac motion reveals non-myocyte regulatory programmes

medRxiv Jul 31, 2026
Genome-wide studies of cardiac structure and function have relied on global imaging metrics that fail to capture the full complexity of myocardial behaviour, leaving the genetic and environmental architecture of motion largely unexplored. Here we sho... read more 
cardiovascular medicine

FMDL-Net: Fourier modulation and dynamic mixing for light field image super-resolution.

Optics letters Aug 1, 2026
Light field imaging suffers from an inherent spatial-angular resolution trade-off. While deep learning has advanced light field image super-resolution (LFISR), convolutional neural networks (CNNs) are limited by local receptive fields that fail to ca... read more 

FMDL-Net: Fourier modulation and dynamic mixing for light field image super-resolution.

Optics letters Aug 1, 2026
Light field imaging suffers from an inherent spatial-angular resolution trade-off. While deep learning has advanced light field image super-resolution (LFISR), convolutional neural networks (CNNs) are limited by local receptive fields that fail to ca... read more 

High-fidelity demodulation of vortex beams through dynamic scattering media using a physically constrained deep neural network.

Optics letters Aug 1, 2026
Vortex beams carrying orbital angular momentum enable high-capacity optical communication and imaging, yet multiple scattering in dynamic media such as biological tissues disrupts their wavefront. Brownian motion decorrelates the scattered field and ... read more 

FMDL-Net: Fourier modulation and dynamic mixing for light field image super-resolution.

Optics letters Aug 1, 2026
Light field imaging suffers from an inherent spatial-angular resolution trade-off. While deep learning has advanced light field image super-resolution (LFISR), convolutional neural networks (CNNs) are limited by local receptive fields that fail to ca... read more 

FMDL-Net: Fourier modulation and dynamic mixing for light field image super-resolution.

Optics letters Aug 1, 2026
Light field imaging suffers from an inherent spatial-angular resolution trade-off. While deep learning has advanced light field image super-resolution (LFISR), convolutional neural networks (CNNs) are limited by local receptive fields that fail to ca... read more 

Machine Learning-Based Prediction of Poor Outcomes in Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis.

Brain and behavior Aug 1, 2026
BACKGROUND: Spontaneous intracerebral hemorrhage (ICH) is associated with high risks of mortality and disability, yet early and accurate outcome prediction remains challenging. This study systematically evaluated the performance of machine learning (... read more 

Classification of tau status with machine learning models in amyloid-positive cohorts.

Alzheimer's & dementia : the journal of the Alzheimer's Association Aug 1, 2026
INTRODUCTION: Although tau positron emission tomography (PET) imaging is effective for staging tau pathology, it is limited clinically by cost and availability. Machine learning models based on magnetic resonance imaging (MRI)- and amyloid PET-derive... read more 
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