A Unified AI Approach for Continuous Monitoring of Human Health and Diseases from Intensive Care Unit to Home with Physiological Foundation Models (UNIPHY+)
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| Main Authors: | , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911165313974272 |
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| author | Wang, Minxiao Kataria, Saurabh Ni, Juntong Buchman, Timothy G. Grunwell, Jocelyn Mai, Mark Jin, Wei Clark, Matthew Brown, Stephanie Fundora, Michael Sharma, Puneet Pan, Tony Khan, Sam Ruchti, Timothy Muthu, Naveen Maher, Kevin Bhavani, Sivasubramanium V Hu, Xiao |
| author_facet | Wang, Minxiao Kataria, Saurabh Ni, Juntong Buchman, Timothy G. Grunwell, Jocelyn Mai, Mark Jin, Wei Clark, Matthew Brown, Stephanie Fundora, Michael Sharma, Puneet Pan, Tony Khan, Sam Ruchti, Timothy Muthu, Naveen Maher, Kevin Bhavani, Sivasubramanium V Hu, Xiao |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_16348 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Unified AI Approach for Continuous Monitoring of Human Health and Diseases from Intensive Care Unit to Home with Physiological Foundation Models (UNIPHY+) Wang, Minxiao Kataria, Saurabh Ni, Juntong Buchman, Timothy G. Grunwell, Jocelyn Mai, Mark Jin, Wei Clark, Matthew Brown, Stephanie Fundora, Michael Sharma, Puneet Pan, Tony Khan, Sam Ruchti, Timothy Muthu, Naveen Maher, Kevin Bhavani, Sivasubramanium V Hu, Xiao Artificial Intelligence 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. |
| title | A Unified AI Approach for Continuous Monitoring of Human Health and Diseases from Intensive Care Unit to Home with Physiological Foundation Models (UNIPHY+) |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2509.16348 |