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Artificial Intelligence

Image: The analytic tool uses a machine learning algorithm to estimate each patient’s likelihood of benefit or harm from CPAP (photo courtesy of 123RF)

AI Tool Estimates CPAP Effect on Cardiovascular Risk in Sleep Apnea

An AI approach predicts individualized cardiovascular benefit or harm from CPAP in sleep apnea, enabling targeted treatment. More...
12 Apr 2026
Image: The method uses data streams commonly available on consumer wearables, including heart rate, physical activity, and oxygen saturation (photo courtesy of 123RF)

Wearable AI Tool Predicts Hospitalization Risk in Heart Failure

An AI approach uses smartwatch data to track fitness and catch declines that precede urgent heart failure care by days to weeks. More...
12 Apr 2026
Graphical Abstract (Akshintala V, Han S, Yan Y, et al. Clinical Gastroenterology and Hepatology, 2026. DOI: 10.1016/j.cgh.2026.03.026)

AI Tool Predicts Post-Therapy Barrett’s Esophagus Recurrence

An AI approach predicts post‑therapy Barrett’s esophagus recurrence and timing, enabling risk‑stratified endoscopic follow‑up. More...
10 Apr 2026
Image: Despite differences in how the ring and the clinical fingertip sensor capture pulse waveforms, the deep learning model predicted vascular age with similar accuracy from both devices. Importantly, ring-derived estimates were associated with blood pressure, a standard cardiovascular health marker (photo courtesy of NUS Medicine)

Wearable AI Tool Estimates Vascular Age for Cardiovascular Risk

An AI approach uses wearable sleep PPG to estimate vascular age, enabling out-of-clinic cardiovascular risk monitoring. More...
09 Apr 2026
Image: Examples of StrivePD Guardian messages (photo courtesy of Rune Labs)

AI Platform Interprets Real-Time Wearable Data for Parkinson’s Management

A new AI system translates continuous wearable data into context-aware guidance to track and manage Parkinson’s symptoms. More...
09 Apr 2026
Image: The algorithm uses geospatial clustering of past cardiac arrests to identify hotspots and guide AED placement within 200 meters to reduce retrieval distance for bystanders (photo credit: 123RF)

Algorithm Identifies Cardiac Arrest Hotspots to Guide AED Placement

A data-driven algorithm targets cardiac arrest clusters to optimize AED placement. More...
08 Apr 2026
Image: Pericardial adipose tissue (PAT) segmentation: A visual comparison of the ground truth segmentations of the PAT (upper row), model’s predictions (middle row) and the subtraction of two masks. From left to the right, columns represent 2D axial slices from upper to lower heart levels and the rightmost column corresponds to the 3D representation of the masked region (Zahra Esmaeili et al. American Journal of Preventive Cardiology (2026). DOI: 10.1016/j.ajpc.2026.101549)

AI Analysis of Pericardial Fat Refines Long-Term Heart Disease Risk

An AI-based method quantifies fat around the heart (pericardial adipose tissue) to sharpen risk estimates without new imaging. More...
01 Apr 2026
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 The Artificial Intelligence channel of HospiMedica keeps the reader informed about the latest news in AI-based clinical decision making, Medical knowledge engineering, Intelligent medical information systems and additional related fields.
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