Artificial Intelligence Medical Compendium

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

Showing 23,771 to 23,780 of 217,366 articles

A biomechanical-constrained temporal learning framework for lightweight skeleton-based exercise recognition.

Scientific reports May 1, 2026
The recognition of exercises using skeletal pose sequences is a significant fitness technology, rehabilitation monitoring, and sports analytics. Nevertheless, the current practices tend to ignore the basic biomechanical processes of human motion. Thi... read more 

TxPert: using multiple knowledge graphs for prediction of transcriptomic perturbation effects.

Nature biotechnology May 1, 2026
Accurately predicting cellular responses to genetic perturbations is essential for understanding disease mechanisms and designing effective therapies. Yet, exhaustively exploring the space of possible perturbations (for example, multigene perturbatio... read more 

Vision Transformer-Based Segmentation of Abdominal Subcutaneous and Visceral Fat on MRI.

Journal of imaging informatics in medicine May 1, 2026
The purpose of this study is to validate a deep learning-based vision transformer for automated quantification and segmentation of abdominal adipose tissue from T1-weighted MRI. This study included abdominal T1 MRI volumes from 107 participants (mean... read more 

Feasibility of No-Code Deep Learning for Diagnosing Bone Metastasis in Bone Scans: A Comparative Study of Teachable Machine and ResNet.

Journal of imaging informatics in medicine May 1, 2026
This study explored the feasibility of developing a model that can diagnose positive and negative bone metastasis from bone scan images using Teachable Machine by Google, a no-code AI platform that does not require programming skills or a GPU environ... read more 

Comparative Clinical Evaluation of "Memory-Efficient" Synthetic 3D Generative Adversarial Networks (GAN) Head-to-Head to State of Art: Results on Computed Tomography of the Chest.

Journal of imaging informatics in medicine May 1, 2026
Generative adversarial networks (GANs) are increasingly used to generate synthetic medical images, addressing the critical shortage of annotated data for training artificial intelligence (AI) systems. This study introduces conditional random field (C... read more 

Recent Advances in Generative AI for Healthcare Applications.

Journal of imaging informatics in medicine May 1, 2026
Artificial intelligence (AI) has catalyzed revolutionary changes across various sectors, notably in healthcare. In particular, generative AI-led by diffusion models and transformer architectures-has enabled significant breakthroughs in medical imagin... read more 

Personalized assessment of hyperuricemia probability in metabolic dysfunction-associated steatotic liver disease: construction and multicenter validation of a clinical nomogram.

BMC gastroenterology May 1, 2026
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease is increasingly recognized as a precursor to secondary hyperuricemia, significantly exacerbating metabolic burden. However, reliable tools for early risk stratification in MASLD pat... read more 

A machine learning framework combining cfDNA fragmentomics and serum biomarkers for early ovarian cancer detection.

Cell communication and signaling : CCS May 1, 2026
BACKGROUND: Ovarian cancer (OC) is a leading cause of cancer-related mortality in women, largely due to the lack of effective strategies for early detection. Here, we aimed to develop a liquid biopsy assay integrating cell-free DNA (cfDNA) fragmentom... read more 

Cognitive Reserve in rural and urban populations: Insights from two aging cohorts in southern India.

Alzheimer's research & therapy May 1, 2026
BACKGROUND: There are no Indian studies estimating Cognitive Reserve (CR) across rural and urban aging populations. METHODS: We estimated CR from two ongoing aging studies in rural (CBR-SANSCOG, n = 4459) and urban (CBR-TLSA, n = 663) southern India.... read more 

Two-staged CT-based radiomics model in characterising early-stage ovarian carcinoma and benign ovarian masses.

Journal of ovarian research May 1, 2026
BACKGROUND: Characterisation of CT detected ovarian masses is challenging with overlapping imaging features, unreliable biomarker or clinical presentation. We proposed a two-staged CT-based radiomics model to identify early-stage ovarian carcinoma (E... read more 
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