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- Publisher Website: 10.1152/physrev.00033.2022
- Scopus: eid_2-s2.0-85163598078
- PMID: 37104717
- WOS: WOS:001034269500002
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Article: LEVERAGING PHYSIOLOGY AND ARTIFICIAL INTELLIGENCE TO DELIVER ADVANCEMENTS IN HEALTH CARE
| Title | LEVERAGING PHYSIOLOGY AND ARTIFICIAL INTELLIGENCE TO DELIVER ADVANCEMENTS IN HEALTH CARE |
|---|---|
| Authors | |
| Keywords | artificial intelligence health care medicine physiology |
| Issue Date | 2023 |
| Citation | Physiological Reviews, 2023, v. 103, n. 4, p. 2423-2450 How to Cite? |
| Abstract | Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: auto-mating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact. |
| Persistent Identifier | http://hdl.handle.net/10722/354281 |
| ISSN | 2023 Impact Factor: 29.9 2023 SCImago Journal Rankings: 10.821 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Zhang, Angela | - |
| dc.contributor.author | Wu, Zhenqin | - |
| dc.contributor.author | Wu, Eric | - |
| dc.contributor.author | Wu, Matthew | - |
| dc.contributor.author | Snyder, Michael P. | - |
| dc.contributor.author | Zou, James | - |
| dc.contributor.author | Wu, Joseph C. | - |
| dc.date.accessioned | 2025-02-07T08:47:38Z | - |
| dc.date.available | 2025-02-07T08:47:38Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.citation | Physiological Reviews, 2023, v. 103, n. 4, p. 2423-2450 | - |
| dc.identifier.issn | 0031-9333 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/354281 | - |
| dc.description.abstract | Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: auto-mating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact. | - |
| dc.language | eng | - |
| dc.relation.ispartof | Physiological Reviews | - |
| dc.subject | artificial intelligence | - |
| dc.subject | health care | - |
| dc.subject | medicine | - |
| dc.subject | physiology | - |
| dc.title | LEVERAGING PHYSIOLOGY AND ARTIFICIAL INTELLIGENCE TO DELIVER ADVANCEMENTS IN HEALTH CARE | - |
| dc.type | Article | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1152/physrev.00033.2022 | - |
| dc.identifier.pmid | 37104717 | - |
| dc.identifier.scopus | eid_2-s2.0-85163598078 | - |
| dc.identifier.volume | 103 | - |
| dc.identifier.issue | 4 | - |
| dc.identifier.spage | 2423 | - |
| dc.identifier.epage | 2450 | - |
| dc.identifier.eissn | 1522-1210 | - |
| dc.identifier.isi | WOS:001034269500002 | - |
