Artificial Intelligence Medical Compendium

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

Showing 22,491 to 22,500 of 216,842 articles

User emotional mechanisms and consumption conversion in AI-generated trend toy blind boxes.

Scientific reports May 6, 2026
Against the backdrop of the rapid diffusion of Artificial Intelligence Generated Content (AIGC) and the rise of the "surprise economy," trendy blind-box toys have emerged as a consumption context characterized by emotional stimulation and community-b... read more 

Validation of remote multimodal AI screening for Parkinson disease across diverse settings.

Communications medicine May 6, 2026
BACKGROUND: Timely detection of Parkinson's disease (PD) remains limited by reliance on in-person neurological evaluations that are often costly and geographically inaccessible. To address these barriers, we develop PARK (Parkinson's Analysis with Re... read more 

Multimodal deep learning prediction of treatment response to anti-vascular endothelial growth factor in diabetic macular oedema.

Eye (London, England) May 6, 2026
OBJECTIVE: To develop and validate a multimodal deep learning model that predicts treatment responses to intravitreal anti-vascular endothelial growth factor (anti-VEGF) injections in patients with diabetic macular oedema (DMO) by combining optical c... read more 

Optimizing cervical cancer diagnosis with a hybrid deep neural network and progressive resizing on pap smear WSIs.

Scientific reports May 6, 2026
Nowadays, computer-aided diagnostic (CAD) systems powered by artificial intelligence (AI) are becoming increasingly prevalent in cervical cancer diagnosis. Automatic selection of features by the deep convolutional neural networks (CNN) is a more prom... read more 

Interpretable modeling to forecast CO2 solid phase boundaries in cryogenic methane rich systems.

Scientific reports May 6, 2026
The unintended formation of solid carbon dioxide during the cryogenic processing of natural gas introduces severe operational hazards, pipeline blockages, and financial losses. To address this critical challenge, this study aims to develop a highly a... read more 

EEG-based harmful brain activity classification using deep learning and feature fusion.

Scientific reports May 6, 2026
The prevalence of research on harmful brain activity has increased, especially since the standardization of electroencephalography (EEG) terminologies. A continual lack of specialists leads to considerable distress and increased mortality rates among... read more 

A novel hybrid NSGA-III and machine learning framework for modeling wheat yield variability using climatic, edaphic, and nutritional drivers.

Scientific reports May 6, 2026
Accurate prediction of crop yield remains a critical research priority due to the increasing vulnerability of agricultural systems to climate change and the growing need for food security. In this study, we developed a hybrid modeling framework to pr... read more 

Machine learning and response surface methodology for optimization and prediction of tribological performance of PLA/rice husk biochar composites.

Scientific reports May 6, 2026
The present study investigates the tribological behaviour of polylactic acid (PLA) composites reinforced with rice husk biochar (RHBC) through an integrated approach combining experimentation, statistical optimization, and machine learning. PLA/RHBC ... read more 

HashEye: a real-time on-drone high-resolution tiny object detection via spatial pruning.

Scientific reports May 6, 2026
While recent deep learning-based object detection has achieved great success in various fields, it remains challenging to find tiny objects in aerial imagery on-the-fly using mobile devices. Since mobile platforms such as drones operate with limited ... read more 

Machine learning-based geospatial assessment of forest structure characteristics and sequestration potential for informed carbon stocks inventories.

Scientific reports May 6, 2026
Managed forest lands are key contributors to the carbon balance assessment needed for the greenhouse gas inventories on local, regional, national, and global levels. However, forest lands, due to size and complexity, are challenging for detailed spat... read more 
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