Artificial Intelligence Medical Compendium

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

Showing 441 to 450 of 213,137 articles

COVLIAS 3.5: integration of attention-based segmentation technique with fuzzy dilated convolutional neural networks for improved classification of chest X-ray scans for multiclass pneumonia diagnosis.

Scientific reports Jul 21, 2026
This study aims to improve pneumonia diagnosis by integrating attention-based U-Net models for lung segmentation with fuzzy logic-enhanced CNNs for classification. This approach addresses the limitations of inadequate modelling of complex spatial rel... read more 

Metabolic Engineering of Microbial Strains for 1,2,4-Butanetriol Production: Progress and Future Perspectives.

Advances in biochemical engineering/biotechnology Jul 21, 2026
Sustainable production of biofuels and biochemicals from renewable biomass represents a promising alternative to fossil-based feedstocks, offering significant benefits for low-carbon economies and environmental protection. The biochemical 1,2,4-butan... read more 

Machine learning-based identification of lactate metabolism-associated biomarkers in non-alcoholic fatty liver disease.

Clinical and experimental medicine Jul 21, 2026
To determine lactate metabolism-associated biomarkers for non-alcoholic fatty liver disease (NAFLD). Based on NAFLD datasets from the gene expression omnibus database and lactate metabolism-related genes from GeneCards database, NAFLD-lactate metabol... read more 

An Interpretable Machine Learning Model for Predicting the Presence of Talaromycosis in HIV Patients Lacking Skin Lesions.

Mycopathologia Jul 21, 2026
INTRODUCTION: The existing predictive models for talaromycosis in people living with HIV without skin lesions are limited by established risk factors and traditional statistical approaches. This study aims to develop an interpretable machine learning... read more 

Advanced prediction of cardiovascular-kidney-metabolic syndrome using eight machine learning models and 24 composite indices.

BMC cardiovascular disorders Jul 21, 2026
AIM: This study aimed to construct and validate a machine learning classifier for cross-sectionally stratifying existing cardiovascular-kidney-metabolic (CKM) syndrome stages using routine composite inflammatory, metabolic and anthropometric indices,... read more 

Environmental and management drivers of gastrointestinal nematodes in shelter dogs across mainland Portugal revealed by ecological niche modelling.

Preventive veterinary medicine Jul 21, 2026
Gastrointestinal nematodes (GIN) are a major health concern in dogs, particularly in high-density environments such as shelters. Toxocara canis, Ancylostoma spp., and Trichuris vulpis are widely distributed, with recognised veterinary and zoonotic re... read more 

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing

arXiv Jul 21, 2026
Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to-image generation and instruction-based image editing. The stack is bu... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG cs.MM eess.IV

Mage-Flow: An Efficient Native-Resolution Foundation Model for Image Generation and Editing

arXiv Jul 21, 2026
Large-scale visual generators are increasingly capable but costly to train, fine-tune, and deploy. We introduce Mage-Flow, a compact 4B-scale generative stack for efficient text-to-image generation and instruction-based image editing. The stack is bu... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG cs.MM eess.IV

Delineate Anything v2: A Global Foundation Model for Field Delineation

arXiv Jul 21, 2026
Accurate agricultural field boundary delineation at large scale is a foundational task for food security, supply chain transparency, and carbon accounting. While vision foundation models like SAM show remarkable zero-shot capabilities, they frequentl... read more 
Computer Vision and Pattern Recognition

Wavefront Parallelization for Efficient Learned Image Compression

arXiv Jul 21, 2026
Autoregressive context models are foundational for learned image compression,but they suffer from slow serial inference. Existing acceleration methods such as checkerboard context require architectural changes and retraining, thus are inapplicable to... read more 
Image and Video Processing cs.CV
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