Artificial Intelligence Medical Compendium

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

Showing 39,901 to 39,910 of 223,737 articles

Transfer learning is the electrocardiogram reconstruction capstone.

Computers in biology and medicine
Electrocardiogram (ECG) reconstruction from reduced-lead configurations is essential for improving patient comfort and enabling wearable cardiac monitoring. Traditional reconstruction models (whether generic, population-specific, or patient-specific)... read more 

Deep learning-based computer-aided diagnosis for parotid gland tumors on MRI.

Auris, nasus, larynx
OBJECTIVE: Accurate imaging-based differentiation of benign and malignant parotid tumors is essential for determining appropriate therapy. We investigated whether a deep learning (DL)-based computer-aided diagnosis (CAD) system provides incremental c... read more 

Prostatic artery embolization for benign prostatic hyperplasia: State of the art.

Diagnostic and interventional imaging
Over the past 25 years, prostatic artery embolization has emerged as a minimally invasive, organ-sparing alternative for managing benign prostatic hyperplasia. Though once considered experimental, it is now endorsed by major international radiologica... read more 

A Novel Quantitative Analysis in Myocardial Perfusion Imaging: How does it compare to the "Golden Eye"?

Zeitschrift fur medizinische Physik
Myocardial Perfusion Imaging is widely used to evaluate left ventricular perfusion in patients with ischemic heart disease. Semi-quantitative scores, such as Total Perfusion Deficit (TPD), are frequently used for the assessment of extent and severity... read more 

Phase diagram and global structure search of bismuth using machine learning potential.

The Journal of chemical physics
Bismuth's (Bi) unique high-pressure phase behavior has long attracted significant interest. Despite their significance in both technological applications and fundamental research, comprehensive and accurate modeling of these transitions remains chall... read more 

Data-driven prediction of ionic conductivity in solid-state electrolytes with machine learning and large language models.

The Journal of chemical physics
Solid-state electrolytes (SSEs) are attractive for next-generation lithium-ion batteries due to improved safety and stability, but their low room-temperature ionic conductivity hinders practical application. Experimental synthesis and testing of new ... read more 

miRBind2 enables sequence-only prediction of miRNA binding and transcript repression

bioRxiv
Motivation: MicroRNAs (miRNAs) regulate gene expression by guiding Argonaute proteins to partially complementary sites on target RNAs. While classical prediction methods rely on engineered features such as seed match categories, evolutionary conserva... read more 

Novel 4D tensor decomposition-based approach integrating tri-omics profiling data can identify functionally relevant gene clusters

bioRxiv
Integrating transcriptome, translatome, and proteome data remains challenging because changes in mRNA, ribosome occupancy, and protein abundance do not always occur simultaneously. To address this, we applied tensor-decomposition-based unsupervised f... read more 

Ancestral state reconstruction with discrete characters using deep learning

bioRxiv
Ancestral state reconstruction is a classical problem of broad relevance in phylogenetics. Likelihood-based methods for reconstructing ancestral states under discrete character models, such as Markov models, have proven extremely useful, but only wor... read more 

BAF complexes maintain accessibility at stimulus-responsive chromatin and are required for transcriptional stimulus responses

bioRxiv
Background Gene expression changes in response to developmental and environmental cues rely on cis-regulatory sequence elements (cREs). BRG1/BRM-Associated Factors (BAF) chromatin remodeling complexes maintain chromatin accessibility at many cREs, en... read more