Artificial Intelligence Medical Compendium

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

Showing 59,111 to 59,120 of 227,876 articles

RaMBat: Accurate identification of medulloblastoma subtypes from diverse data sources with severe batch effects.

Molecular oncology
As the most common pediatric brain malignancy, medulloblastoma (MB) includes multiple distinct molecular subtypes characterized by clinical heterogeneity and genetic alterations. Accurate identification of MB subtypes is essential for downstream risk... read more 

SLC25A45: a gatekeeper for methylated amino acid metabolism.

Trends in endocrinology and metabolism: TEM
The metabolite substrates of numerous transporters remain largely elusive. Two recent studies by Khan et al. and Dias et al. identify SLC25A45 as a mitochondrial transporter of methylated amino acids that supports de novo carnitine synthesis, providi... read more 

Automated High-Throughput Raman Spectral Framework for Cellular Differentiation Monitoring.

Nano letters
High-throughput, label-free monitoring of cellular differentiation remains a major challenge in stem cell biology and regenerative medicine. Raman spectroscopy offers rich molecular specificity without perturbing the cell state, but the analytical co... read more 

Immune Checkpoint Activity and Prognostic Roles of TNFRSF8, CD160, and TNFSF9 in Primary and Brain Metastatic NSCLC.

Asia-Pacific journal of clinical oncology
Here, we utilized advanced bioinformatics approaches alongside experimental validation to identify key prognostic biomarkers and potential immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC). Our findings highlight distinct diff... read more 

Managing Conflict of Interest in Clinical Practice Guidelines With Artificial Intelligence: Insights From Large Language Models and Beyond.

Journal of evidence-based medicine
BACKGROUND: Conflict of interest (COI) management is critical for ensuring the scientific integrity and fairness of clinical practice guidelines (CPGs). Large language models (LLMs) have great potential in strengthening COI management, particularly i... read more 

ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning.

Nature communications
Co-fractionation mass spectrometry (CF-MS) enables large-scale profiling of endogenous protein-protein interactions, yet CF-MS data generation is of low throughput and therefore predictive models are often limited by the scarcity and limited diversit... read more 

Evaluating single-cell ATAC-seq atlasing technologies using sequence-to-function modeling.

Nature communications
Deciphering the cis-regulatory logic underlying cell type identity remains a key challenge in biology. Single-cell chromatin accessibility (scATAC-seq) atlases enable training of sequence-to-function (S2F) deep learning models to decode enhancer logi... read more 

Hierarchical maturation of structural brain connectomes from birth to childhood.

Nature communications
The postnatal white matter connectome undergoes profound reorganization, yet the topological principles governing its spatiotemporal maturation remain largely unknown. Using connectome mapping, machine learning, and neurobiological annotation, we sho... read more 

The dataset for extending EMNIST evaluation.

Scientific data
The paper describes the dataset for a deeper evaluation of the machine learning models for handwritten character recognition. For that purpose, we build a dataset that, combined with existing NIST Databases, offers possibilities for additional analys... read more 

Identification of Chlamydia pneumoniae and NLRP3 inflammasome activation in Alzheimer's disease retina.

Nature communications
Chlamydia pneumoniae is an intracellular bacterium implicated in Alzheimer's disease (AD), but its role in retinal pathology and disease progression is unclear. Here we identify Chlamydia pneumoniae inclusions in the retina, showing higher burden in ... read more