Artificial Intelligence to Diagnose Complications of Diabetes.

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Title: Artificial Intelligence to Diagnose Complications of Diabetes.
Authors: Ayers AT; Diabetes Technology Society, Burlingame, CA, USA., Ho CN; Diabetes Technology Society, Burlingame, CA, USA., Kerr D; Center for Health Systems Research, Sutter Health, Santa Barbara, CA, USA., Cichosz SL; Department of Health Science and Technology, Aalborg University, Aalborg, Denmark., Mathioudakis N; School of Medicine, Johns Hopkins University, Baltimore, MD, USA., Wang M; University of California, San Francisco, San Francisco, CA, USA., Najafi B; Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA.; Center for Advanced Surgical and Interventional Technology (CASIT), Department of Surgery, Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, USA., Moon SJ; Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, Republic of Korea., Pandey A; Division of Cardiology and Geriatrics, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA., Klonoff DC; Diabetes Technology Society, Burlingame, CA, USA.; Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA, USA.
Source: Journal of diabetes science and technology [J Diabetes Sci Technol] 2025 Jan; Vol. 19 (1), pp. 246-264. Date of Electronic Publication: 2024 Nov 22.
Publication Type: Journal Article; Review; Research Support, N.I.H., Extramural
Journal Info: Publisher: Sage Country of Publication: United States NLM ID: 101306166 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1932-2968 (Electronic) Linking ISSN: 19322968 NLM ISO Abbreviation: J Diabetes Sci Technol Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: Artificial Intelligence to Diagnose Complications of Diabetes.
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  Data: <searchLink fieldCode="AU" term="%22Ayers+AT%22">Ayers AT</searchLink>; Diabetes Technology Society, Burlingame, CA, USA.<br /><searchLink fieldCode="AU" term="%22Ho+CN%22">Ho CN</searchLink>; Diabetes Technology Society, Burlingame, CA, USA.<br /><searchLink fieldCode="AU" term="%22Kerr+D%22">Kerr D</searchLink>; Center for Health Systems Research, Sutter Health, Santa Barbara, CA, USA.<br /><searchLink fieldCode="AU" term="%22Cichosz+SL%22">Cichosz SL</searchLink>; Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.<br /><searchLink fieldCode="AU" term="%22Mathioudakis+N%22">Mathioudakis N</searchLink>; School of Medicine, Johns Hopkins University, Baltimore, MD, USA.<br /><searchLink fieldCode="AU" term="%22Wang+M%22">Wang M</searchLink>; University of California, San Francisco, San Francisco, CA, USA.<br /><searchLink fieldCode="AU" term="%22Najafi+B%22">Najafi B</searchLink>; Michael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, TX, USA.; Center for Advanced Surgical and Interventional Technology (CASIT), Department of Surgery, Geffen School of Medicine, University of California, Los Angeles (UCLA), Los Angeles, CA, USA.<br /><searchLink fieldCode="AU" term="%22Moon+SJ%22">Moon SJ</searchLink>; Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, School of Medicine, Sungkyunkwan University, Seoul, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Pandey+A%22">Pandey A</searchLink>; Division of Cardiology and Geriatrics, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA.<br /><searchLink fieldCode="AU" term="%22Klonoff+DC%22">Klonoff DC</searchLink>; Diabetes Technology Society, Burlingame, CA, USA.; Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA, USA.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Sage%22">Sage </searchLink><i>Country of Publication: </i>United States <i>NLM ID: </i>101306166 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1932-2968 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2219322968%22">19322968 </searchLink><i>NLM ISO Abbreviation: </i>J Diabetes Sci Technol <i>Subsets: </i>MEDLINE
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        Value: 10.1177/19322968241287773
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        Text: English
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      – TitleFull: Artificial Intelligence to Diagnose Complications of Diabetes.
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              Text: 2025 Jan
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