View in EDS

Deep learning-enabled ECG system for detecting left ventricular hypertrophy and predicting cardiovascular prognoses.

Saved in:
Bibliographic Details
Title: Deep learning-enabled ECG system for detecting left ventricular hypertrophy and predicting cardiovascular prognoses.
Authors: Yang ZY; Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China.; Graduate Institute of Medical Sciences, National Defense Medical University, Taipei, Taiwan, Republic of China., Hsing SC; Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China., Tsai DJ; Medical Technology Education Center, School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China., Lin C; Medical Technology Education Center, School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China.; Artificial Intelligence of Things Center, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, Republic of China.; School of Public Health, National Defense Medical University, Taipei, Taiwan, Republic of China.; Department of Education and Research, Taipei City Hospital, Taipei, Taiwan, Republic of China., Lin CS; Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China., Wang CH; Department of Otolaryngology-Head and Neck Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, Republic of China.; Graduate Institute of Medical Sciences, National Defense Medical University, Taipei, Taiwan, Republic of China., Fang WH; Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China. rumaf.fang@gmail.com.; Artificial Intelligence of Things Center, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, Republic of China. rumaf.fang@gmail.com.; Department of Education and Research, Taipei City Hospital, Taipei, Taiwan, Republic of China. rumaf.fang@gmail.com.
Source: BioData mining [BioData Min] 2026 Mar 04; Vol. 19 (1). Date of Electronic Publication: 2026 Mar 04.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101319161 Publication Model: Electronic Cited Medium: Print ISSN: 1756-0381 (Print) Linking ISSN: 17560381 NLM ISO Abbreviation: BioData Min Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
FullText Text:
  Availability: 0
Header DbId: mdl
DbLabel: MEDLINE Ultimate
An: 41781965
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Deep learning-enabled ECG system for detecting left ventricular hypertrophy and predicting cardiovascular prognoses.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AU" term="%22Yang+ZY%22">Yang ZY</searchLink>; Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China.; Graduate Institute of Medical Sciences, National Defense Medical University, Taipei, Taiwan, Republic of China.<br /><searchLink fieldCode="AU" term="%22Hsing+SC%22">Hsing SC</searchLink>; Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China.<br /><searchLink fieldCode="AU" term="%22Tsai+DJ%22">Tsai DJ</searchLink>; Medical Technology Education Center, School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China.<br /><searchLink fieldCode="AU" term="%22Lin+C%22">Lin C</searchLink>; Medical Technology Education Center, School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China.; Artificial Intelligence of Things Center, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, Republic of China.; School of Public Health, National Defense Medical University, Taipei, Taiwan, Republic of China.; Department of Education and Research, Taipei City Hospital, Taipei, Taiwan, Republic of China.<br /><searchLink fieldCode="AU" term="%22Lin+CS%22">Lin CS</searchLink>; Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China.<br /><searchLink fieldCode="AU" term="%22Wang+CH%22">Wang CH</searchLink>; Department of Otolaryngology-Head and Neck Surgery, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, Republic of China.; Graduate Institute of Medical Sciences, National Defense Medical University, Taipei, Taiwan, Republic of China.<br /><searchLink fieldCode="AU" term="%22Fang+WH%22">Fang WH</searchLink>; Division of Family Medicine, Department of Family and Community Medicine, Tri-Service General Hospital, and School of Medicine, National Defense Medical University, Taipei, Taiwan, Republic of China. rumaf.fang@gmail.com.; Artificial Intelligence of Things Center, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, Republic of China. rumaf.fang@gmail.com.; Department of Education and Research, Taipei City Hospital, Taipei, Taiwan, Republic of China. rumaf.fang@gmail.com.
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22101319161%22">BioData mining</searchLink> [BioData Min] 2026 Mar 04; Vol. 19 (1). <i>Date of Electronic Publication: </i>2026 Mar 04.
– Name: TypePub
  Label: Publication Type
  Group: TypPub
  Data: Journal Article
– Name: TitleSource
  Label: Journal Info
  Group: Src
  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22BioMed+Central%22">BioMed Central </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101319161 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Print <i>ISSN: </i>1756-0381 (Print) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2217560381%22">17560381 </searchLink><i>NLM ISO Abbreviation: </i>BioData Min <i>Subsets: </i>PubMed not MEDLINE
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=41781965
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1186/s13040-026-00536-2
    Languages:
      – Code: eng
        Text: English
    Titles:
      – TitleFull: Deep learning-enabled ECG system for detecting left ventricular hypertrophy and predicting cardiovascular prognoses.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Yang ZY
      – PersonEntity:
          Name:
            NameFull: Hsing SC
      – PersonEntity:
          Name:
            NameFull: Tsai DJ
      – PersonEntity:
          Name:
            NameFull: Lin C
      – PersonEntity:
          Name:
            NameFull: Lin CS
      – PersonEntity:
          Name:
            NameFull: Wang CH
      – PersonEntity:
          Name:
            NameFull: Fang WH
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 04
              M: 03
              Text: 2026 Mar 04
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 1756-0381
          Numbering:
            – Type: volume
              Value: 19
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: BioData mining
              Type: main
ResultId 1