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Illness severity assessment of older adults in critical illness using machine learning (ELDER-ICU): an international multicentre study with subgroup bias evaluation.
Liu, Xiaoli; Hu, Pan; Yeung, Wesley; Zhang, Zhongheng; Ho, Vanda; Liu, Chao; Dumontier, Clark; Thoral, Patrick J; Mao, Zhi; Cao, Desen; Mark, Roger G; Zhang, Zhengbo; Feng, Mengling; Li, Deyu; Celi, Leo Anthony.
Affiliation
  • Liu X; School of Biological Science and Medical Engineering, Beihang University, Beijing, China; Center for Artificial Intelligence in Medicine, Chinese PLA General Hospital, Beijing, China; Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of T
  • Hu P; Department of Anesthesiology, The 920 Hospital of Joint Logistic Support Force of Chinese PLA, Kunming Yunnan, China; Department of Critical Care Medicine, The First Medical Center of PLA General Hospital, Beijing, China.
  • Yeung W; Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Cardiology, National University Heart Centre, Singapore.
  • Zhang Z; Department of Emergency Medicine, Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
  • Ho V; Division of Geriatric Medicine, Department of Medicine, National University Hospital, Singapore.
  • Liu C; Department of Critical Care Medicine, The First Medical Center of PLA General Hospital, Beijing, China.
  • Dumontier C; New England Geriatric Research Education and Clinical Center, VA Boston Healthcare System, Boston, MA, USA; Division of Aging, Brigham and Women's Hospital, Boston, MA, USA.
  • Thoral PJ; Center for Critical Care Computational Intelligence, Department of Intensive Care Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands.
  • Mao Z; Department of Critical Care Medicine, The First Medical Center of PLA General Hospital, Beijing, China.
  • Cao D; Department of Biomedical Engineering, Chinese PLA General Hospital, Beijing, China.
  • Mark RG; Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Zhang Z; Center for Artificial Intelligence in Medicine, Chinese PLA General Hospital, Beijing, China.
  • Feng M; Saw Swee Hock School of Public Health and the Institute of Data Science, National University of Singapore, Singapore.
  • Li D; School of Biological Science and Medical Engineering, Beihang University, Beijing, China; National Key Lab for Virtual Reality Technology and Systems, Beihang University, Beijing, China. Electronic address: deyuli@buaa.edu.cn.
  • Celi LA; Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA; Department of Biostatistics, Harvard T H Chan School of Public Health, Bos
Lancet Digit Health ; 5(10): e657-e667, 2023 10.
Article in En | MEDLINE | ID: mdl-37599147
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Full text: 1 Database: MEDLINE Main subject: Critical Illness / Frailty Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Humans Country/Region as subject: America do norte Language: En Year: 2023 Type: Article
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Full text: 1 Database: MEDLINE Main subject: Critical Illness / Frailty Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Humans Country/Region as subject: America do norte Language: En Year: 2023 Type: Article