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Artificial Intelligence Deep Learning Methods in the Assessment of Cardiovascular Risk for Patients With Autoimmune Diseases: A Promising Prospect.

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Title: Artificial Intelligence Deep Learning Methods in the Assessment of Cardiovascular Risk for Patients With Autoimmune Diseases: A Promising Prospect.
Authors: Strube T; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide SA, Australia; Royal Adelaide Hospital, Adelaide SA, Australia. Electronic address: taylor.strube@sa.gov.au., Leslie A; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide SA, Australia; Royal Adelaide Hospital, Adelaide SA, Australia., Stretton B; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide SA, Australia; Royal Adelaide Hospital, Adelaide SA, Australia., Bacchi S; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide SA, Australia; Lyell McEwin Hospital, Elizabeth Vale SA, Australia; Flinders University, Bedford Park SA, Australia.
Source: Heart, lung & circulation [Heart Lung Circ] 2026 May; Vol. 35 (5), pp. e78-e79.
Publication Type: Letter
Journal Info: Publisher: Elsevier Australia Country of Publication: Australia NLM ID: 100963739 Publication Model: Print Cited Medium: Internet ISSN: 1444-2892 (Electronic) Linking ISSN: 14439506 NLM ISO Abbreviation: Heart Lung Circ Subsets: MEDLINE; In Process
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Strube+T%22">Strube T</searchLink>; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide SA, Australia; Royal Adelaide Hospital, Adelaide SA, Australia. Electronic address: taylor.strube@sa.gov.au.<br /><searchLink fieldCode="AU" term="%22Leslie+A%22">Leslie A</searchLink>; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide SA, Australia; Royal Adelaide Hospital, Adelaide SA, Australia.<br /><searchLink fieldCode="AU" term="%22Stretton+B%22">Stretton B</searchLink>; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide SA, Australia; Royal Adelaide Hospital, Adelaide SA, Australia.<br /><searchLink fieldCode="AU" term="%22Bacchi+S%22">Bacchi S</searchLink>; Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide SA, Australia; Lyell McEwin Hospital, Elizabeth Vale SA, Australia; Flinders University, Bedford Park SA, Australia.
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  Data: <searchLink fieldCode="JN" term="%22100963739%22">Heart, lung & circulation</searchLink> [Heart Lung Circ] 2026 May; Vol. 35 (5), pp. e78-e79.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Australia%22">Elsevier Australia </searchLink><i>Country of Publication: </i>Australia <i>NLM ID: </i>100963739 <i>Publication Model: </i>Print <i>Cited Medium: </i>Internet <i>ISSN: </i>1444-2892 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2214439506%22">14439506 </searchLink><i>NLM ISO Abbreviation: </i>Heart Lung Circ <i>Subsets: </i>MEDLINE; In Process
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      – Type: doi
        Value: 10.1016/j.hlc.2025.11.011
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      – Code: eng
        Text: English
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        StartPage: e78
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      – TitleFull: Artificial Intelligence Deep Learning Methods in the Assessment of Cardiovascular Risk for Patients With Autoimmune Diseases: A Promising Prospect.
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            – D: 01
              M: 05
              Text: 2026 May
              Type: published
              Y: 2026
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              Value: 1444-2892
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              Value: 35
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              Value: 5
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            – TitleFull: Heart, lung & circulation
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