Artificial Intelligence Medical Compendium

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

Showing 21,681 to 21,690 of 216,624 articles

Pan-FM: A Pan-Organ Foundation Model with Saliency-Guided Masking for Missing Robustness

arXiv May 8, 2026
Foundation models (FMs) have shown great promise in medical imaging, but most FMs are trained on unimodal data within isolated domains, such as brain MRI alone. Human aging and disease arise through coordinated biological processes across organs, the... read more 
Computer Vision and Pattern Recognition cs.AI

Causal EpiNets: Precision-corrected Bounds on Individual Treatment Effects using Epistemic Neural Networks

arXiv May 8, 2026
Individual treatment effects are not point-identified from data. The Probability of Necessity and Sufficiency (PNS) circumvents this limitation by characterizing individual-level causality through intersection bounds derived from combined experimenta... read more 
Machine Learning cs.AI cs.LG econ.EM

A shared neural code for gender across faces, bodies, and objects in the human brain

bioRxiv May 8, 2026
Humans can readily infer gender from diverse visual categories, including faces, bodies, and objects, yet it remains unclear whether the brain constructs a shared, category-general representation of gender. To fill the gap, we measured neural respons... read more 
neuroscience

A widespread internal brain state for fentanyl withdrawal

bioRxiv May 8, 2026
Opioid addiction is characterized by escalating drug use, driven in part by negative reinforcement from withdrawal, but the neural processes linking withdrawal to increased drug-taking remain poorly understood. Here, we use multisite local field pote... read more 
neuroscience

Cholesteryl Ester as a Prognostic Biomarker In IDH-wildtype Glioblastoma

bioRxiv May 8, 2026
Current treatment of IDH-wildtype glioblastoma (GBM) relies on the first-line chemotherapy-temozolomide. Although MGMT methylation is routinely conducted to predict chemosensitivity, its efficacy is often compromised. Thus, there is an urgent need to... read more 
neuroscience

Neural Network Guided Calibration for Fast Virtual Twin Generation in Cardiovascular ODE Models

bioRxiv May 8, 2026
Calibration of closed-loop lumped-parameter cardiovascular models remains a major bottleneck for scalable digital-twin generation because inverse estimation is ill-conditioned and typically requires computationally expensive iterative forward simulat... read more 
physiology

Input data when using neural networks to estimate lower-body torques from wearable sensors during gait: Is it of great influence?

bioRxiv May 8, 2026
Recent advancements in wearable sensors and machine learning show promise for estimating lower-body joint torques outside of laboratory settings. Inertial Measurement Units combined with Convolutional Neural Networks have proven effective for this ta... read more 
bioengineering

TopoFuseNet: Hierarchical Graph Representation Learning with Multi-Scale Topological Features for Accurate Drug Synergy Prediction

bioRxiv May 8, 2026
Accurate prediction of drug synergy is paramount for developing effective combination therapies and advancing personalized medicine. Although methods based on graph neural networks (GNNs) have become a prevalent approach, they often treat molecules a... read more 
bioinformatics

BRIDGE: A Multi-organ Histo-ST Foundation Model Enables Virtual Spatial Transcriptomics for Enhanced Few-shot Cancer Diagnosis

bioRxiv May 8, 2026
Recent studies have explored generating virtual spatial transcriptomics (ST) profiles from histological images, offering a promising alternative to laboratory-measured molecular profiling. However, existing approaches predominantly rely on single-org... read more 
genomics

STARMAP: A 3D-informed framework for mapping functional regions in proteins to regulatory and cellular phenotypes

bioRxiv May 8, 2026
Artificial Intelligence (AI) has transformed biology by revealing patterns in large-scale datasets and predicting regulatory relationships. Yet even the most advanced models often fail to identify biologically meaningful mechanisms from statistical a... read more 
genomics
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