Artificial Intelligence Medical Compendium

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

Showing 49,731 to 49,740 of 224,814 articles

A dataset of harmonized global air quality monitoring metadata.

Scientific data
This study addresses the gap in air quality monitoring metadata reporting by building a classifier for air quality station types and area characteristics. It leverages ultra-high-resolution land cover data, complemented by additional demographic and ... read more 

Different BI-RADS breast cancer diagnosis using MobileNetV1 and vision transformer based on explainable artificial intelligence (XAI).

Scientific reports
Breast cancer (BC) remains one of the leading causes of death among women in the world, depending on the requirement for precise, effective, and interpretable computer-aided diagnosis systems (CADs). In this work, a hybrid deep learning (DL) framewor... read more 

A novel AI-coupled flow chamber method quantifying erythrocyte osmotic fragility.

Scientific reports
Osmotic fragility (OF) is widely used to evaluate red blood cell (RBC) membrane stability, water transport dynamics and hemoglobinopathies, traditionally via spectrophotometric, visual, or flow cytometric techniques. Here, we present a novel flow cha... read more 

Evaluating Sentinel-2 gap filling techniques for cloud removal and data reconstruction.

Scientific reports
Cloud cover creates frequent data gaps in high-resolution satellite imagery, particularly from Sentinel-2. These disrupt its continuity and reliability for time-sensitive applications such as water resource management, irrigation scheduling and crop ... read more 

Assessment and AI-Based Prediction of Complications in Reduction Mammoplasty: A Combined Statistical and Fuzzy Inference Approach in a 10-Year Cohort from Tehran Hospitals (2013-2023).

Aesthetic plastic surgery
INTRODUCTION: Gigantomastia causes physical, psychological, and dermatological issues, often with ptosis; reduction mammoplasty effectively relieves symptoms but carries minor (self-limiting or medically managed) and major (surgically requiring) comp... read more 

A machine learning model for optimizing treatment of patients with poorly controlled type 2 diabetes.

Communications medicine
BACKGROUND: Cardiorenal-protective sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and glucagon-like peptide-1 receptor agonists (GLP-1RA) lack selection guidance. We aimed to build a SGLT-2i/GLP-1RA Decision Score (TiP DecScore) to tailor select... read more