Artificial Intelligence Medical Compendium

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

Showing 40,351 to 40,360 of 223,737 articles

Interpretable CRAM‑Enhanced Lightweight Dual‑Branch CNN for Real‑Time Breast Cancer Histopathology in Internet‑of‑Medical‑Things Environments.

Small (Weinheim an der Bergstrasse, Germany)
Breast cancer remains a primary global health concern, with histopathological image analysis serving as the diagnostic gold standard. However, manual microscopy is time-consuming and often subjective. While deep learning offers a powerful solution, e... read more 

Percutaneous coronary intervention in high bleeding risk patients: a review of contemporary management strategies.

Expert review of cardiovascular therapy
INTRODUCTION: High bleeding risk (HBR) affects over one-third of patients undergoing percutaneous coronary intervention (PCI) and is associated with elevated mortality due to both hemorrhagic and ischemic complications. Optimizing management of these... read more 

Advances in Electrocardiogram-Based Non-Invasive Blood Glucose Monitoring Technology.

Diabetes, obesity & metabolism
Blood glucose monitoring is fundamental to diabetes management, yet traditional invasive methods are limited by patient discomfort and infection risks. In recent years, electrocardiogram (ECG), a conventional tool for cardiovascular assessment, has g... read more 

Artificial Intelligence in Type 1 Diabetes Management: A Scoping Review of Randomised Controlled Trials.

Diabetes, obesity & metabolism
BACKGROUND: Artificial intelligence is emerging in healthcare systems. In type 1 diabetes, AI-enabled tools are increasingly used to support nutrition assessment and insulin decision-making, yet their clinical utility and safety remain unclear. METHO... read more 

Artificial Intelligence in Pediatric Oncology in Africa: A Survey of Awareness, Use, and Readiness Amongst Healthcare Workers.

Pediatric blood & cancer
INTRODUCTION: Artificial intelligence (AI) has the potential to enhance oncology diagnostics, treatment planning, and patient monitoring. In pediatric oncology, AI can support both clinical care and research. The roles and awareness of AI in African ... read more 

TransCNN: a hybrid deep learning model for detecting honey adulteration by LED-induced fluorescence spectroscopy.

Analytical methods : advancing methods and applications
In recent years, honey products have faced increasing issues of adulteration, posing significant challenges to their authenticity and quality. LED-induced fluorescence (LED-IF) has the characteristics of being non-destructive, rapid and efficient, of... read more