Higher blood biochemistry-based biological age developed by advanced deep learning techniques is associated with frailty in geriatric rehabilitation inpatients: RESORT.

Abstract

Authors

• Lihuan Guan
  Department of Medicine and Aged Care, @AgeMelbourne, The Royal Melbourne Hospital, The University of Melbourne, Victoria, Australia; Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore. Electronic address: lihuan.guan1@unimelb.edu.au.
• Camilla S L Tuttle
  Department of Medicine and Aged Care, @AgeMelbourne, The Royal Melbourne Hospital, The University of Melbourne, Victoria, Australia; Department of Surgery, St Vincent's Hospital, The University of Melbourne, Victoria, Australia. Electronic address: camilla.tuttle@unimelb.edu.au.
• Fedor Galkin
  InSilico Medicine, Science Park, Hong Kong; Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, UK.
• Alex Zhavoronkov
  Pharmaceutical Artificial Intelligence Department, Insilico Medicine, Inc., Emerging Technology Centers, Johns Hopkins University at Eastern, Baltimore, Maryland, USA.
• Andrea B Maier
  Department of Medicine and Aged Care, @AgeMelbourne, The Royal Melbourne Hospital, The University of Melbourne, Victoria, Australia; Department of Human Movement Sciences, @AgeAmsterdam, Faculty of Behavioural and Movement Sciences, Vrije Universiteit, Amsterdam Movement Sciences, Amsterdam, the Netherlands.; Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Centre for Healthy Longevity, @AgeSingapore, National University Health System, Singapore. Electronic address: a.maier@nus.edu.sg.

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