Advancing healthcare practice and education via data sharing: demonstrating the utility of open data by training an artificial intelligence model to assess cardiopulmonary resuscitation skills.

Autor: Constable MD; Department of Psychology, Northumbria University, Northumberland Building, College Lane, Newcastle Upon Tyne, NE1 8SG, UK. merryn.constable@northumbria.ac.uk., Zhang FX; Department of Computer Science, Durham University, Durham, UK., Conner T; Department of Nursing and Midwifery, Northumbria University, Newcastle Upon Tyne, UK., Monk D; Department of Nursing and Midwifery, Northumbria University, Newcastle Upon Tyne, UK., Rajsic J; Department of Psychology, Northumbria University, Northumberland Building, College Lane, Newcastle Upon Tyne, NE1 8SG, UK., Ford C; Department of Nursing and Midwifery, Northumbria University, Newcastle Upon Tyne, UK., Park LJ; Department of Nursing and Midwifery, Northumbria University, Newcastle Upon Tyne, UK., Platt A; Department of Nursing and Midwifery, Northumbria University, Newcastle Upon Tyne, UK., Porteous D; Department of Nursing and Midwifery, Northumbria University, Newcastle Upon Tyne, UK., Grierson L; Department of Family Medicine, McMaster University, Hamilton, Canada., Shum HPH; Department of Computer Science, Durham University, Durham, UK.
Jazyk: angličtina
Zdroj: Advances in health sciences education : theory and practice [Adv Health Sci Educ Theory Pract] 2024 Sep 09. Date of Electronic Publication: 2024 Sep 09.
DOI: 10.1007/s10459-024-10369-5
Abstrakt: Health professional education stands to gain substantially from collective efforts toward building video databases of skill performances in both real and simulated settings. An accessible resource of videos that demonstrate an array of performances - both good and bad-provides an opportunity for interdisciplinary research collaborations that can advance our understanding of movement that reflects technical expertise, support educational tool development, and facilitate assessment practices. In this paper we raise important ethical and legal considerations when building and sharing health professions education data. Collective data sharing may produce new knowledge and tools to support healthcare professional education. We demonstrate the utility of a data-sharing culture by providing and leveraging a database of cardio-pulmonary resuscitation (CPR) performances that vary in quality. The CPR skills performance database (collected for the purpose of this research, hosted at UK Data Service's ReShare Repository) contains videos from 40 participants recorded from 6 different angles, allowing for 3D reconstruction for movement analysis. The video footage is accompanied by quality ratings from 2 experts, participants' self-reported confidence and frequency of performing CPR, and the demographics of the participants. From this data, we present an Automatic Clinical Assessment tool for Basic Life Support that uses pose estimation to determine the spatial location of the participant's movements during CPR and a deep learning network that assesses the performance quality.
(© 2024. Crown.)
Databáze: MEDLINE
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