Artificial Intelligence Medical Compendium

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

Showing 64,081 to 64,090 of 231,309 articles

A Benchmark Dataset for Satellite-Based Estimation and Detection of Rain.

Scientific data Jan 15, 2026
Accurately tracking the global distribution of precipitation is essential for both research and operational meteorology. Satellite observations remain the only means of achieving consistent, global precipitation monitoring. While machine learning has... read more 

Skin disease diagnostics through federated transfer learning on heterogeneous data.

Scientific reports Jan 15, 2026
Skin diseases frequently cause mental and physical distress and are major global health concern. Because early detection is crucial to successful treatment, accurate diagnosis is challenge for dermatologists as well. Diagnostic accuracy could be sign... read more 
Humans Neural Networks, Computer Machine Learning Databases, Factual Deep Learning Skin Diseases

MicroRNAs in oncology: a translational perspective in the era of AI.

Nature reviews. Clinical oncology Jan 15, 2026
Over the past three decades, knowledge of microRNA (miRNA) biology has advanced from the initial discovery of their regulatory functions to the finding of abnormal activity in leukaemias, and then to a comprehensive understanding of the roles of miRN... read more 

Optimized CatBoost machine learning (OCML) for DDoS detection in cloud virtual machines with time-series and adversarial robustness.

Scientific reports Jan 15, 2026
Distributed Denial of Service (DDoS) attacks represent one of the most strategically executed and severe threats in cloud computing, often leading to substantial data loss and significant financial damage for both cloud service providers and their us... read more 

Active guidance in ultrasound bladder scanning using reinforcement learning.

Scientific reports Jan 15, 2026
Accurate measurement of bladder volume is essential for diagnosing urinary retention and voiding dysfunction. However, finding optimal view can be challenging for less experienced operators, potentially leading to suboptimal imaging and potential mis... read more 

Cross-well machine learning prediction of sonic logs in Newfoundland and Labrador.

Scientific reports Jan 15, 2026
Predicting compressional slowness (DTCO) from non-sonic logs can reduce acquisition cost, fill data gaps, and support field planning. We evaluate blind cross-well DTCO prediction on two offshore Newfoundland & Labrador wells using a strictly leakage-... read more 

Interpreting artificial neural network-based modeling of 4 H-SiC mosfets using explainable AI.

Scientific reports Jan 15, 2026
Wide bandgap (WBG) semiconductors such as 4 H-SiC MOSFETs are key enablers for next-generation power electronics due to their superior efficiency and high-temperature capability. However, their electrical performance is strongly affected by process v... read more 

Increasing engagement with cognitive-behavioral therapy (CBT) using generative AI: a randomized controlled trial (RCT).

Communications medicine Jan 15, 2026
BACKGROUND: Shortages in mental healthcare lead to long periods of inadequate support for many patients. While digital interventions offer a scalable solution to this unmet clinical need, patient engagement remains a key challenge. Generative artific... read more 

Distribution of device-measured 24-h movement behaviors in older adults: cross-sectional findings from the HUNT4 study.

Scientific reports Jan 15, 2026
Comprehensive mapping of key physical activity (PA) types, postures, and sleep among older adults is important for informing public health policies and interventions. This study aimed to describe the 24-h time distribution of key PA types, postures, ... read more 

Modeling Ischemic Stroke Pathological Dynamics via Continuous Fields and Vector Flow.

NPJ digital medicine Jan 15, 2026
Precise localization of perfusion deficits in diffusion-weighted MRI (DWI) is critical for acute ischemic stroke management. However, existing deep learning methods typically produce discrete binary masks, failing to capture the continuous nature of ... read more 
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