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AI in evaluating ambulation of stroke patients: severity classification with video and functional ambulation category scale.

Jeong-Hyun KimHyeon HongKyuwon LeeYeji JeongHokyoung RyuHyundo KimSeong-Ho JangHyeng-Kyu ParkJae-Young HanHye Jung ParkHasuk BaeByung-Mo OhWon-Seok KimSang Yoon LeeShi-Uk Lee
Published in: Topics in stroke rehabilitation (2024)
This confirms the potential of utilizing human posture estimation based on vision data not only to develop gait parameter models but also to develop models to classify severity according to the FAC criteria used by physicians. To develop an AI-based severity classification model, a large amount and variety of data is necessary and data collected in non-standardized real environments, not in laboratories, can also be used meaningfully.
Keyphrases
  • electronic health record
  • big data
  • artificial intelligence
  • machine learning
  • deep learning
  • primary care
  • endothelial cells
  • induced pluripotent stem cells
  • cerebral palsy