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. |
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| 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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