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Images in a 75-year-old woman who underwent routine screening mammography in 2022. Left mediolateral oblique views shown from prior screening mammograms: (A) 2015, (B) 2018, (C) 2019, and (D) 2021. In (E) 2022, a new mass developed in the left breast at the 6-o’clock position (arrow), with a (F) corresponding irregular mass at US (arrow). Subsequent US-guided core needle biopsy yielded invasive ductal carcinoma, grade 2. The deep learning 5-year risk scores gradually increased from 2.0 (2015) to 2.1 (2018), 3.4 (2019), 3.6 (2021), and 15.3 (2022). CMFN = centimeters from nipple, LT = left, TRANS = transverse (Photo courtesy of Radiological Society of North America)

AI Tool Predicts Five-Year Breast Cancer Risk from Mammograms

An AI approach analyzes serial mammograms to predict five-year breast cancer risk, outperforming traditional calculators. More...
24 Jun 2026
Image: The AI-derived score estimates hypertension-related damage across multiple organs before a major cardiovascular event (Image credit: iStock

AI Risk Score Reveals Hidden Hypertension-Related Organ Damage

An AI approach profiles hypertension-related multi-organ injury and flags stroke, heart failure, and CKD risk. More...
24 Jun 2026
Image: The three-dimensional scan is divided into a series of two-dimensional images, which are then broken down into smaller sections along the tissue surface. The AI algorithm assesses for each of these sections how much the tissue differs from healthy tissue (Photo courtesy of Fraunhofer Austria)

Rapid AI OCT System Detects Malignant Liver Tissue Intraoperatively

An AI approach using OCT flags liver tumor tissue within seconds, offering 81% accuracy for faster intraoperative decisions. More...
24 Jun 2026
Image: Overall architecture of the proposed framework. (A) Model development using VAE with adversarial training to remove demographic attributes from ECGs. (B) Performance analysis for downstream tasks. (C) Applications of the privacy-preserving ECG embeddings in clinical outcome prediction and secure data sharing. (Fairuz Shadmani Shishir et al., Scientific Reports (2026). DOI: 10.1038/s41598-026-47665-6)

Privacy-Preserving AI Protects Sensitive Information in ECG Data

An AI approach shields age/sex/race signals in ECGs while preserving LVEF, LVH, and 5-year mortality risk prediction. More...
24 Jun 2026
Image: The AI-derived score estimates hypertension-related damage across multiple organs before a major cardiovascular event (Image credit: iStock

AI Risk Score Reveals Hidden Hypertension-Related Organ Damage

An AI approach profiles hypertension-related multi-organ injury and flags stroke, heart failure, and CKD risk. More...
24 Jun 2026
Image: Overall architecture of the proposed framework. (A) Model development using VAE with adversarial training to remove demographic attributes from ECGs. (B) Performance analysis for downstream tasks. (C) Applications of the privacy-preserving ECG embeddings in clinical outcome prediction and secure data sharing. (Fairuz Shadmani Shishir et al., Scientific Reports (2026). DOI: 10.1038/s41598-026-47665-6)

Privacy-Preserving AI Protects Sensitive Information in ECG Data

An AI approach shields age/sex/race signals in ECGs while preserving LVEF, LVH, and 5-year mortality risk prediction. More...
24 Jun 2026
Image: Comparative multimodal calibration of patient-specific atrial fibrillation models: Impact of imaging and electrophysiology data on arrhythmogenic substrate identification (Mahmoud Ehnesh et al., The Journal of Physiology (2026). DOI: 10.1113/jp290765)

Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation

A patient-specific digital twin heart model integrating MRI and electroanatomic data guides more targeted AF ablation. More...
23 Jun 2026
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