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A New Method Using Deep Learning to Predict the Response to Cardiac Resynchronization Therapy.

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Title: A New Method Using Deep Learning to Predict the Response to Cardiac Resynchronization Therapy.
Authors: Larsen K; Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, USA., He Z; Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA., de A Fernandes F; Nuclear Medicine Department, Hospital Universitario Antonio Pedro-EBSERH-UFF, Niteroi, Brazil., Zhang X; Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road 300, Nanjing, Jiangsu, 210029, China., Zhao C; Department of Computer Science, Kennesaw State University, Marietta, GA, USA., Sha Q; Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, USA., Mesquita CT; Nuclear Medicine Department, Hospital Universitario Antonio Pedro-EBSERH-UFF, Niteroi, Brazil., Paez D; Nuclear Medicine and Diagnostic Imaging Section, Division of Human Health, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria., Garcia EV; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA., Zou J; Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road 300, Nanjing, Jiangsu, 210029, China. jgzou@njmu.edu.cn., Peix A; Nuclear Medicine Department, Institute of Cardiology, 17 No. 702La Habana, Vedado, CP10 400, , Cuba. atpeix@gmail.com., Hung GU; Department of Nuclear Medicine, Chang Bing Show Chwan Memorial Hospital, Changhua, Taiwan., Zhou W; Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA. whzhou@mtu.edu.; Center for Biocomputing and Digital Health, Institute of Computing and Cybersystems, and Health Research Institute, Michigan Technological University, 1400 Townsend Drive, Houghton, MI, 49931, USA. whzhou@mtu.edu.
Source: Journal of imaging informatics in medicine [J Imaging Inform Med] 2025 Dec; Vol. 38 (6), pp. 4029-4045. Date of Electronic Publication: 2025 Feb 20.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 9918663679206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2948-2933 (Electronic) Linking ISSN: 29482925 NLM ISO Abbreviation: J Imaging Inform Med Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: A New Method Using Deep Learning to Predict the Response to Cardiac Resynchronization Therapy.
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  Data: <searchLink fieldCode="AU" term="%22Larsen+K%22">Larsen K</searchLink>; Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, USA.<br /><searchLink fieldCode="AU" term="%22He+Z%22">He Z</searchLink>; Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA.<br /><searchLink fieldCode="AU" term="%22de+A+Fernandes+F%22">de A Fernandes F</searchLink>; Nuclear Medicine Department, Hospital Universitario Antonio Pedro-EBSERH-UFF, Niteroi, Brazil.<br /><searchLink fieldCode="AU" term="%22Zhang+X%22">Zhang X</searchLink>; Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road 300, Nanjing, Jiangsu, 210029, China.<br /><searchLink fieldCode="AU" term="%22Zhao+C%22">Zhao C</searchLink>; Department of Computer Science, Kennesaw State University, Marietta, GA, USA.<br /><searchLink fieldCode="AU" term="%22Sha+Q%22">Sha Q</searchLink>; Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, USA.<br /><searchLink fieldCode="AU" term="%22Mesquita+CT%22">Mesquita CT</searchLink>; Nuclear Medicine Department, Hospital Universitario Antonio Pedro-EBSERH-UFF, Niteroi, Brazil.<br /><searchLink fieldCode="AU" term="%22Paez+D%22">Paez D</searchLink>; Nuclear Medicine and Diagnostic Imaging Section, Division of Human Health, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna, Austria.<br /><searchLink fieldCode="AU" term="%22Garcia+EV%22">Garcia EV</searchLink>; Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA.<br /><searchLink fieldCode="AU" term="%22Zou+J%22">Zou J</searchLink>; Department of Cardiology, The First Affiliated Hospital of Nanjing Medical University, Guangzhou Road 300, Nanjing, Jiangsu, 210029, China. jgzou@njmu.edu.cn.<br /><searchLink fieldCode="AU" term="%22Peix+A%22">Peix A</searchLink>; Nuclear Medicine Department, Institute of Cardiology, 17 No. 702La Habana, Vedado, CP10 400, , Cuba. atpeix@gmail.com.<br /><searchLink fieldCode="AU" term="%22Hung+GU%22">Hung GU</searchLink>; Department of Nuclear Medicine, Chang Bing Show Chwan Memorial Hospital, Changhua, Taiwan.<br /><searchLink fieldCode="AU" term="%22Zhou+W%22">Zhou W</searchLink>; Department of Applied Computing, Michigan Technological University, Houghton, MI, 49931, USA. whzhou@mtu.edu.; Center for Biocomputing and Digital Health, Institute of Computing and Cybersystems, and Health Research Institute, Michigan Technological University, 1400 Townsend Drive, Houghton, MI, 49931, USA. whzhou@mtu.edu.
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  Data: <searchLink fieldCode="JN" term="%229918663679206676%22">Journal of imaging informatics in medicine</searchLink> [J Imaging Inform Med] 2025 Dec; Vol. 38 (6), pp. 4029-4045. <i>Date of Electronic Publication: </i>2025 Feb 20.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer+Nature%22">Springer Nature </searchLink><i>Country of Publication: </i>Switzerland <i>NLM ID: </i>9918663679206676 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2948-2933 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2229482925%22">29482925 </searchLink><i>NLM ISO Abbreviation: </i>J Imaging Inform Med <i>Subsets: </i>MEDLINE
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        Value: 10.1007/s10278-024-01380-8
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              Text: 2025 Dec
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