Noninvasive continuous blood pressure prediction using FlexNIRS and machine learning during carotid endarterectomy.

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Bibliographic Details
Title:	Noninvasive continuous blood pressure prediction using FlexNIRS and machine learning during carotid endarterectomy.
Authors:	Einalou Z; Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States., Dadgostar M; Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States., Wu KC; Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States., Martin A; Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States., Robinson MB; Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States., Renna M; Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States., Qu JZ; Massachusetts General Hospital, Harvard Medical School, Department of Anesthesia, Critical Care and Pain Medicine, Boston, Massachusetts, United States., Sunwoo J; Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States., Franceschini MA; Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Boston, Massachusetts, United States.
Source:	Journal of biomedical optics [J Biomed Opt] 2025 Feb; Vol. 30 (Suppl 2), pp. S23913. Date of Electronic Publication: 2025 Sep 19.
Publication Type:	Journal Article
Journal Info:	Publisher: Published by SPIE--the International Society for Optical Engineering in cooperation with International Biomedical Optics Society Country of Publication: United States NLM ID: 9605853 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1560-2281 (Electronic) Linking ISSN: 10833668 NLM ISO Abbreviation: J Biomed Opt Subsets: MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1560-2281
DOI:	10.1117/1.JBO.30.S2.S23913