mlsanityData to 14 Oct 2026

A Unified AI Approach for Continuous Monitoring of Human Health and Diseases from Intensive Care Unit to Home with Physiological Foundation Models (UNIPHY+)

arXiv 2509.16348 ↗First posted 19 Sep 2025cs.AIcited by 2

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Abstract (arXiv)

We present UNIPHY+, a unified physiological foundation model (physioFM) framework designed to enable continuous human health and diseases monitoring across care settings using ubiquitously obtainable physiological data. We propose novel strategies for incorporating contextual information during pretraining, fine-tuning, and lightweight model personalization via multi-modal learning, feature fusion-tuning, and knowledge distillation. We advocate testing UNIPHY+ with a broad set of use cases from intensive care to ambulatory monitoring in order to demonstrate that UNIPHY+ can empower generalizable, scalable, and personalized physiological AI to support both clinical decision-making and long-term health monitoring.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 14 of its 37 references that are in the map. First posted on arXiv 19 Sep 2025.

Builds on

14 of 37 references.

References · 14

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  2. 2021On the Opportunities and Risks of Foundation Modelscited by 4,033
  3. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 2,039
  4. 2020Knowledge Distillation: A Surveycited by 1,603
  5. 2024Chronos: Learning the Language of Time Seriescited by 759
  6. 2017Gated Multimodal Units for Information Fusioncited by 248
  7. 2018Adversarial Reprogramming of Neural Networkscited by 116
  8. 2021Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Seriescited by 96
  9. 2023Large-scale Training of Foundation Models for Wearable Biosignalscited by 95
  10. 2024Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogramcited by 84
  11. 2021Self-supervised representation learning from 12-lead ECG datacited by 80
  12. 2024PaPaGei: Open Foundation Models for Optical Physiological Signalscited by 69
2 more
  1. 2023LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation -- Extended Versioncited by 50
  2. 2025Pulse-PPG: An Open-Source Field-Trained PPG Foundation Model for Wearable Applications Across Lab and Field Settingscited by 37

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Generalist vs Specialist Time Series Foundation Models: Investigating Potential Emergent Behaviors in Assessing Human Health Using PPG Signalscited by 2
  2. 2026Exposing Vulnerabilities in Explanation for Time Series Classifiers via Dual-Target Attackscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026Physiological World Models for Human State Transitions
  2. 2024PhilHumans: Benchmarking Machine Learning for Personal Health
  3. 2026VitalAgent: A Tool-Augmented Agent for Reactive and Proactive Physiological Monitoring over Wearable Health Data
  4. 2026Simulating clinical interventions with a generative multimodal model of human physiology
  5. 2025BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals
  6. 2026HealthLoopQA: A Context-Aware Question Answering Benchmark for Interpreting Wearable Monitoring Data in Diabetes Care
  7. 2026Toward World Modeling of Physiological Signals with Chaos-Theoretic Balancing and Latent Dynamics
  8. 2023From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models