Artificial Intelligence Medical Compendium

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

Showing 54,951 to 54,960 of 226,183 articles

DBSOMA: A Machine Learning Method that Identifies Chemical Modulators of Transcriptional States Uncovers Effectors of Beta-Cell Maturation

bioRxiv
The effects of perturbation on a biological system can be readily measured in terms of transcriptional changes. However, despite a wealth of transcriptional perturbation response data, there are currently few methods to draw equivalence between the m... read more 

METEOR: joint genome-scale reconstruction and enzyme prediction

bioRxiv
Motivation: Current machine learning methods for enzyme function prediction primarily treat proteins as independent entities, ignoring the metabolic context in which they operate. This reductionist approach often generates biologically implausible an... read more 

Transcriptomics-based modeling of methionine metabolism effectively estimates sample-wise DNA methylation activity and epigenetic aging

bioRxiv
DNA methylation is a central epigenetic modification that regulates gene expression, maintains genomic stability, and guides cellular differentiation. However, direct measurements of DNA methylation, such as whole genome bisulfite sequencing or DNA m... read more 

Neural Networks as Entropic Systems: Applications in Digital Pathology

bioRxiv
Deep learning systems in digital pathology are widely regarded as opaque, limiting clinical trust and interpretability. We present a framework for empirically characterizing training-time learning dynamics in neural networks by directly measuring act... read more 

BIG-TB: A benchmark for evaluating prediction and interpretability of sequence-based machine learning using *Mycobacterium tuberculosis* genomes

bioRxiv
Foundation models aim to learn useful representations of biological sequences. However, the applicability of these representations for a wide range of tasks, including phenotype prediction and variant discovery, is still in question, in large part du... read more 

Physics-Informed Neural Network for Mapping Vascular and Tissue Dynamics Using Laser Speckle Contrast Imaging

bioRxiv
Significance: Quantitatively mapping both cerebral blood flow and tissue dynamics from laser speckle contrast imaging (LSCI) is powerful for studying cerebral blood flow in general and neural-vascular coupling and stroke in particular. Conventional m... read more 

GRAVITY: Dynamic gene regulatory network-enhanced RNA velocity modeling for trajectory inference and biological discovery

bioRxiv
RNA velocity techniques have emerged as efficient tools for unraveling the complex trajectories of cell development and differentiation. However, most of existing RNA velocity approaches are constrained by estimating transcriptional parameters for ea... read more 

Modularity-dependent storage of dynamic spiking patterns: bridging micro- and mesoscopic representations

bioRxiv
Biological systems rely on asynchronous and temporally overlapping dynamics, allowing for the concurrent activation of multiple processes. This principle is particularly evident in brain function, where cognitive tasks engage distributed, interacting... read more 

Socially Grounded Exemplars Improve Synthetic Conversations for Health-Related Social Needs Navigation

medRxiv
Health-Related Social Needs (HRSNs) significantly impact health outcomes, yet traditional care often fails to address them effectively. While conversational agents offer scalable support, their deployment is hindered by privacy risks and a lack of sp... read more 

Artificial intelligence-assisted real-time nasopharyngeal cancer diagnostic model enhances rhinologist performance: a prospective multi-reader study.

Annals of medicine
BACKGROUND: Nasopharyngeal carcinoma (NPC) poses significant diagnostic challenges due to the anatomical complexity of the nasopharynx and reliance on endoscopic visual interpretation, often leading to delayed detection and unnecessary biopsies. Alth... read more