arXiv Machine Learning

Attractor Image-Based Deep Learning of Arterial Pulse Waves for Age Classification

arXiv:2608. 12117v1 Announce Type: new Abstract: Arterial pulse waveform morphology evolves with age, reflecting structural and functional changes in the cardiovascular system.

arXiv Machine Learning

Jun 10

DMT: Demographic Conditioning, Morphology-Enhanced Transformer for Cuffless Blood Pressure Estimation from PPG Signals

arXiv:2606. 11125v1 Announce Type: cross Abstract: Blood pressure (BP) is a key marker for cardiovascular risk assessment and therapeutic decision-making, and Photoplethysmography (PPG) enables low-cost, wearable-friendly cuffless BP estimation.

By Yidan Shen, Neville Mathew, Maham Rahimi, Deependra Dhakal, George Zouridakis, Xin Fu, Renjie Hu

llms

arXiv AI

Jun 19

Modeling Day-Long ECG Signals to Predict Heart Failure Risk with Explainable AI

arXiv:2601. 00014v2 Announce Type: replace-cross Abstract: Heart failure (HF) affects 11.

By Eran Zvuloni, Ronit Almog, Michael Glikson, Shany Brimer Biton, Ilan Green, Izhar Laufer, Offer Amir, Joachim A. Behar

arXiv AI

Jul 9

Non-contact, Real-time, Heart-rate Measurement using Image Processing with Commodity Cameras and AI Agents

arXiv:2607. 06598v1 Announce Type: cross Abstract: Heart rate measurement is one of the key requirements for real-time health monitoring, in particular for health caring of elderly people.

By Kelly Li, Fulu Li

agents

arXiv AI

Jul 28

Blood Pressure Estimation from PPG: A Comparative Study of Direct and ECG-Mediated Deep Learning Pipelines

arXiv:2607. 23406v1 Announce Type: cross Abstract: Continuous cuffless blood pressure (BP) monitoring is essential for connected health systems and wearable devices, enabling early detection, longitudinal tracking, and personalized management of cardiovascular disease.

By Bo Wu, Haoling Wang, Zhuodiao Kuang, Kateryna Shapovalenko

benchmarks

arXiv Machine Learning

Jul 28

Aortic Valve Disease Screening from PPG via Physiology-Guided Self-Supervised Learning

arXiv:2602. 04266v2 Announce Type: replace-cross Abstract: Aortic valve disease (AVD) represents a major public health burden, while its diagnosis relies on echocardiography, which is limited by cost and specialist expertise, restricting scalable screening and risk stratification.

By Jiaze Wang, Qinghao Zhao, Zizheng Chen, Zhejun Sun, Deyun Zhang, Yuxi Zhou, Shenda Hong

fine-tuning

arXiv Machine Learning

Jun 25

Pulmonary Embolism Risk Stratification from CTPA and Medical Records: Vascular Graphs Are Not All You Need

arXiv:2606. 25956v1 Announce Type: cross Abstract: Risk stratification for pulmonary embolism (PE) is critical for clinical decision-making.

By Nathan Painchaud, Tristan Hab\'emont, Morgane des Ligneris, Allan Serva, Pierre Croisille, Laurent Bertoletti, Thomas Lampert, Johannes F. Lutzeyer, Odyss\'ee Merveille

benchmarks

arXiv AI

Jul 14

MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms

arXiv:2607. 09749v1 Announce Type: cross Abstract: Foundation models have recently emerged as a powerful paradigm for learning transferable representations from large scale biomedical data, yet existing approaches for physiological waveforms primarily optimize reconstruction or forecasting objectives that do not explicitly preserve clinically meaningful waveform morphology.

By Saiyang Feng, Yuanyun Zhang, Shi Li

rag multimodal safety

arXiv AI

Jun 2

A Novel Data Augmentation Strategy for Robust Deep Learning Classification of Biomedical Time-Series Data: Application to ECG and EEG Analysis

arXiv:2507. 12645v1 Announce Type: cross Abstract: The increasing need for accurate and unified analysis of diverse biological signals, such as ECG and EEG, is paramount for comprehensive patient assessment, especially in synchronous monitoring.

By Mohammed Guhdar, Ramadhan J. Mstafa, Abdulhakeem O. Mohammed

benchmarks

arXiv Machine Learning

Jul 3

Scaling to Multimodal and Multichannel Heart Sound Classification with Synthetic and Augmented Biosignals

arXiv:2509. 11606v4 Announce Type: replace-cross Abstract: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for approximately 17.

By Milan Marocchi, Matthew Fynn, Kayapanda Mandana, Yue Rong

llms diffusion fine-tuning multimodal benchmarks

arXiv Machine Learning

Jul 28

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction

arXiv:2607. 23412v1 Announce Type: new Abstract: Electrocardiograms (ECGs) are widely used for cardiovascular risk prediction, yet models often fail to transfer across hospitals because of protocol, population, and measurement differences.

By Jie Lin, Weijie Sun, Sunil V. Kalmady, Anita Khalafbeigi, Abram Hindle, Padma Kaul, Russell Greiner

benchmarks

arXiv AI

Jul 3

Contrastive Deep Learning Reveals Age Biomarkers in Histopathological Skin Biopsies

arXiv:2411. 16956v2 Announce Type: replace-cross Abstract: As global life expectancy increases, so does the burden of chronic diseases, yet individuals exhibit considerable variability in the rate at which they age.

By Kaustubh Chakradeo (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark), Pernille Nielsen (Technical University of Denmark, Department of Applied Mathematics and Computer Science, Denmark), Lise Mette Rahbek Gjerdrum (Department of Pathology, Copenhagen University Hospital- Zealand University Hospital, Roskilde, Denmark, Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark), Gry Sahl Hansen (Department of Pathology, Copenhagen University Hospital- Zealand University Hospital, Roskilde, Denmark), David A Duch\^ene (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark), Laust H Mortensen (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark, Danmarks Statistik, Denmark), Majken K Jensen (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark), Samir Bhatt (University of Copenhagen, Section of Epidemiology, Department of Public Health, Copenhagen, Denmark, Imperial College London, United Kingdom)

arXiv AI

Jun 16

Automated ultrasound doppler angle estimation using deep learning

arXiv:2508. 04243v2 Announce Type: replace-cross Abstract: Angle estimation is an important step in the Doppler ultrasound clinical workflow to measure blood velocity.

By Nilesh Patil, Ajay Anand

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