Artificial Intelligence Medical Compendium

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

Showing 17,431 to 17,440 of 213,726 articles

Physics-Informed Neural Networks for Parameter Recovery in the Repressilator Oscillatory Model

bioRxiv May 15, 2026
Parameter estimation in nonlinear biological dynamical systems is a difficult inverse problem because the governing equations are often stiff or oscillatory, the data are sparse and noisy, and the objective landscape is non-convex. Physics-informed n... read more 
bioinformatics

Comparison of Machine Learning Surrogate Models for Prediction of Single-Fiber Activation in Deep Brain Stimulation

bioRxiv May 15, 2026
Machine-learning surrogate models are positioned to help optimize deep brain stimulation (DBS) usage by predicting neural activation in response to electrical stimulation, while minimizing tradeoffs between computational expense and accuracy. Previou... read more 
neuroscience

Bio-BLIP: A Multimodal Architecture for Transferable Reasoning in Genomic Variant Interpretation

bioRxiv May 15, 2026
Developing scientific hypotheses in biology requires integrating heterogeneous evidence across DNA sequence, gene context, protein function, and prior literature. Existing multimodal AI systems expose biological evidence to reasoning models through t... read more 
genomics

Human-like sequential sound-to-meaning transfer drives artificial speech comprehension

bioRxiv May 15, 2026
Artificial intelligence has reached a pivotal threshold. Multimodal large models can approach human-level speech comprehension by rapidly transforming sound into meaning. However, whether this process relies on human-like mechanisms remains unknown. ... read more 
neuroscience

Deep learning models for chemical perturbation prediction do not yet utilise drug molecular features

bioRxiv May 15, 2026
Recent deep learning models for L1000 chemical perturbation prediction incorporate dedicated drug molecular encoders. We retrained seven such models from scratch with zeroed or shuffled drug inputs, and compared them with a multilayer perceptron that... read more 
bioinformatics

S2F-agent: Skill-grounded agent for Sequence-to-Function computational genomics workflows

bioRxiv May 15, 2026
Sequence-to-Function (S2F) foundation models are revolutionizing genomic research, yet their fragmented ecosystem severely bottlenecks practical application by incompatible inputs, outputs, and runtime environments. General-purpose coding agents lack... read more 
bioinformatics

Tsallis-Gated Autoencoder: A Nonextensive Physics-Informed Approach for Unsupervised Anomaly Detection in Glioblastoma Multiforme RNA-seq Data

bioRxiv May 15, 2026
Glioblastoma multiforme (GBM) is characterised by profound genomic heterogeneity and heavy-tailed gene-expression distributions that challenge conventional machine-learning methods. We introduce the Tsallis-Gated Autoencoder (Tsallis-GAE), a physics-... read more 
bioinformatics

Identification of non-covalent inhibitors for the atypical peroxiredoxin PRDX5 as a therapeutic strategy in malignant pleural mesothelioma

bioRxiv May 15, 2026
Malignant pleural mesothelioma (MPM) is an aggressive asbestos-linked cancer with limited therapeutic options and a dismal 5-year survival rate of ~5%. While aberrant production of reactive oxygen and nitrogen species (ROS/RNS) is a hallmark of MPM, ... read more 
cancer biology

Deep Learning for Cross-Domain Spatial Transcriptomic Modeling of Tissue Repair

bioRxiv May 15, 2026
Spatial transcriptomics enables investigation of tissue organization while preserving molecular and spatial information within intact tissues. However, existing computational methods primarily focus on clustering and batch integration and provide lim... read more 
bioinformatics

Emergent representations of graphical structure in mechanistic neural models of causal judgment

bioRxiv May 15, 2026
Humans have a remarkable ability to judge causal relationships from a limited number of unreliable observations. Past work on causal cognition has largely focused on normative accounts of human behavior, leaving unknown how biologically plausible neu... read more 
neuroscience
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