Artificial Intelligence Medical Compendium

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

Showing 23,581 to 23,590 of 217,176 articles

GNN-ML-FRL: a graph-enhanced meta-adaptive federated learning framework for scalable pest identification and ernvironmental modeling.

Scientific reports May 1, 2026
Heterogeneous agro-ecological factors, insect breeding, and climate change are serious challenges to sustainable agricultural management. The study proposes a graph-enhanced meta-adaptive federated learning framework (GNN-ML-FRL) to address the chall... read more 

A hybrid simulation-machine learning proxy model for waterflood design optimization in the Bahariya Formation.

Scientific reports May 1, 2026
This study presents a novel hybrid methodology combining machine learning (ML) with conventional reservoir simulation to optimize waterflooding in the geologically complex Bahariya Formation, Western Desert, Egypt. The research addresses the critical... read more 

Data-driven assessment of industrial influences on urban heat index dynamics across Telangana, India.

Scientific reports May 1, 2026
Urban heat stress is an escalating environmental risk in rapidly industrialising regions of India, where land-use transformation and industrial expansion interact with background climatic warming. This study examines the spatio-temporal evolution of ... read more 

The impact of AI technology for ideological and political education teaching based on deep learning.

Scientific reports May 1, 2026
This study investigates the innovative use of deep learning models in ideological and political education (IPE) at vocational colleges. The study focuses on addressing two core challenges in traditional IPE: limited adaptability of educational resour... read more 

Data-driven prioritization of carbon neutral strategies using agentic artificial intelligence and fractal fuzzy decision analysis.

Scientific reports May 1, 2026
This study proposes an integrated decision-making framework to prioritize carbon-neutral strategies under complex and uncertain conditions. The model combines an agentic artificial intelligence structure, which systematically extracts relevant strate... read more 

A hybrid flower pollination algorithm-deep learning approach for strength prediction of sustainable recycled fine aggregate concrete with GUI-based implementation.

Scientific reports May 1, 2026
This study presents an integrated experimental-machine learning framework for evaluating and predicting the compressive strength of sustainable rigid pavement concrete incorporating 50% washed recycled fine aggregates (WRFA) as a replacement for natu... read more 

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 
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