Artificial Intelligence Medical Compendium

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

Showing 551 to 560 of 213,137 articles

Diagnostic Accuracy of MRI Radiomics for Predicting KRAS Mutation in Rectal Cancer: A Systematic Review and Meta-analysis

medRxiv Jul 20, 2026
BackgroundKRAS mutation status is an important biomarker in rectal cancer, with implications for prognosis and treatment response. MRI-based radiomics has emerged as a non-invasive approach for predicting tumor genotypes. However, the diagnostic perf... read more 
radiology and imaging

FloREN: Decoding Immune Regulatory Networks through Interpretable Graph Transformer Patient Representations.

bioRxiv Jul 20, 2026
Single-cell RNA sequencing (scRNA-seq) enables detailed characterization of cellular heterogeneity, yet understanding the full cellular and regulatory environment of complex tissues remains challenging. In the era of large single-cell atlases, this t... read more 
bioinformatics

From Hodgkin-Huxley to Pretrained Neural Inference AI

bioRxiv Jul 20, 2026
High-density probes record from thousands of neurons simultaneously, yet resolving single-neuron identity remains an ill-posed inverse problem. While detailed simulations precisely characterize the biophysical forward process, their utility for inter... read more 
neuroscience

Closed-loop control of in vitro neuronal activity using reinforcement learning after in silico pre-training

bioRxiv Jul 20, 2026
Controlling specific neuronal dynamics with electrical stimulation is critical for therapeutic neuromodulation, yet deriving optimal control policies remains challenging due to the complex and non-stationary nature of biological neuronal networks. Wh... read more 
neuroscience

Ensembles of in silico structures enable T cell peptide-MHC binding prediction

bioRxiv Jul 20, 2026
Adaptive immunity relies on T-cell receptor (TCR) recognition of peptides presented by the major histocompatibility complex (pMHC). Accurate prediction of TCR:pMHC binding pairs from sequence data remains a longstanding challenge in computational imm... read more 
immunology

GDTR: Layer-wise Settling Depth Reveals Biological Grammar in Genomic Foundation Models

bioRxiv Jul 20, 2026
Genomic foundation models capture sequence regularities, yet existing interpretability tools rarely ask where in the layer stack a biological grammar becomes stable. We introduce GDTR, the Genomic Deep-Thinking Ratio, a training-free residual-stream ... read more 
bioinformatics

Factorization and spatial encodings: a hypothesis about the foundations of the genomic code

bioRxiv Jul 20, 2026
The genomic mechanisms that efficiently encode the initial architecture and synaptic connectivity of neural circuits remain poorly understood. We hypothesise that two primary mechanisms -- spatial encoding and factorisation -- enable a limited genome... read more 
neuroscience

Interpretable Peripheral Blood Cell Classification via Vision-Language Concept Bottleneck and Soft Decision Tree

bioRxiv Jul 20, 2026
Motivation: Deep learning classifiers for medical image analysis typically function as black boxes, disclosing neither the image features underlying their predictions nor the reasoning by which individual decisions are reached. Peripheral blood cell ... read more 
bioinformatics

Deep learning framework for kinematic event detection and stimulation decoding in primate reaching behavior

bioRxiv Jul 20, 2026
Accurate analysis of motor behavior requires the reliable detection of ongoing kinematic events and a granular characterization of the changes in motor output that occur in response to neural impairments. This article describes a deep learning framew... read more 
animal behavior and cognition

When does more data help? Spectral Geometry and Scaling Laws in MRI Transformers

bioRxiv Jul 20, 2026
Scaling laws describe how model performance improves as the amount of training data increases, and recent theories such as the zeta law suggest that scaling behavior is influenced by the eigenspectrum of the model's latent representation. Here, we ev... read more 
neuroscience
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