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Non-invasive classification of coronary perfusion pressure during CPR using smartphone-based skin video and deep learning.

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Title: Non-invasive classification of coronary perfusion pressure during CPR using smartphone-based skin video and deep learning.
Authors: Kwon S; Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 08826, Republic of Korea; Integrated Major in Innovative Medical Science, Graduate School, Seoul National University, Seoul 03080, Republic of Korea., Shin DA; Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul 03080, Republic of Korea., Kim T; Research Center for Disaster Medicine, Medical Research Center, Seoul National University, Seoul 03080, Republic of Korea; Department of Emergency Medicine, Seoul National University Hospital, Seoul 03080, Republic of Korea., Kim KS; Research Center for Disaster Medicine, Medical Research Center, Seoul National University, Seoul 03080, Republic of Korea; Department of Emergency Medicine, Seoul National University Hospital, Seoul 03080, Republic of Korea., Suh GJ; National Medical Center, Seoul 04564, Republic of Korea., Sim J; Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea., Hur S; Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Blue Robin inc., Seoul, 06524, Republic of Korea., Park J; Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Advanced Institute of Convergence Technology (AICT), Suwon 16229, Republic of Korea., Lee JC; Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 08826, Republic of Korea; Research Center for Disaster Medicine, Medical Research Center, Seoul National University, Seoul 03080, Republic of Korea; Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Department of Biomedical Engineering and Innovative Medical Technology Research Institute, Seoul National University Hospital, Seoul 03080, Republic of Korea. Electronic address: ljch@snu.ac.kr.
Source: Computer methods and programs in biomedicine [Comput Methods Programs Biomed] 2026 Jul; Vol. 281, pp. 109348. Date of Electronic Publication: 2026 Apr 02.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Scientific Publishers Country of Publication: Ireland NLM ID: 8506513 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-7565 (Electronic) Linking ISSN: 01692607 NLM ISO Abbreviation: Comput Methods Programs Biomed Subsets: MEDLINE
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  Data: Non-invasive classification of coronary perfusion pressure during CPR using smartphone-based skin video and deep learning.
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  Data: <searchLink fieldCode="AU" term="%22Kwon+S%22">Kwon S</searchLink>; Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 08826, Republic of Korea; Integrated Major in Innovative Medical Science, Graduate School, Seoul National University, Seoul 03080, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Shin+DA%22">Shin DA</searchLink>; Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul 03080, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+T%22">Kim T</searchLink>; Research Center for Disaster Medicine, Medical Research Center, Seoul National University, Seoul 03080, Republic of Korea; Department of Emergency Medicine, Seoul National University Hospital, Seoul 03080, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+KS%22">Kim KS</searchLink>; Research Center for Disaster Medicine, Medical Research Center, Seoul National University, Seoul 03080, Republic of Korea; Department of Emergency Medicine, Seoul National University Hospital, Seoul 03080, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Suh+GJ%22">Suh GJ</searchLink>; National Medical Center, Seoul 04564, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Sim+J%22">Sim J</searchLink>; Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Hur+S%22">Hur S</searchLink>; Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Blue Robin inc., Seoul, 06524, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Park+J%22">Park J</searchLink>; Graduate School of Convergence Science and Technology, Seoul National University, Seoul 08826, Republic of Korea; Advanced Institute of Convergence Technology (AICT), Suwon 16229, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lee+JC%22">Lee JC</searchLink>; Interdisciplinary Program in Bioengineering, Graduate School, Seoul National University, Seoul 08826, Republic of Korea; Research Center for Disaster Medicine, Medical Research Center, Seoul National University, Seoul 03080, Republic of Korea; Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul 03080, Republic of Korea; Department of Biomedical Engineering and Innovative Medical Technology Research Institute, Seoul National University Hospital, Seoul 03080, Republic of Korea. Electronic address: ljch@snu.ac.kr.
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        Value: 10.1016/j.cmpb.2026.109348
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              Text: 2026 Jul
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