Using machine learning to address data accuracy and information integrity in digital health delivery
Version 2 2024-06-04, 00:32Version 2 2024-06-04, 00:32
Version 1 2017-05-09, 14:26Version 1 2017-05-09, 14:26
conference contribution
posted on 2024-06-04, 00:32authored byZZ Sako, V Karpathiou, Sasan AdibiSasan Adibi, N Wickramasinghe
Today, much of healthcare delivery is digital. In particular, there exists a plethora of mHealth solutions being developed. This in turn necessitates the need for accurate data and information integrity if superior mHealth is to ensue. Lack of data accuracy and information integrity can cause serious harm to patients and limit the benefits of mHealth technology. The described exploratory case study serves to investigate data accuracy and information integrity in mHealth, with the aim of incorporating Machine Learning to detect sources of inaccurate data and deliver quality information.
History
Pagination
301-318
Location
Bled, Slovenia
Start date
2016-06-19
End date
2016-06-22
Language
eng
Publication classification
E1 Full written paper - refereed, E Conference publication
Copyright notice
2016, The Authors
Title of proceedings
Bled 2016 : Digital Economy Proceedings of the 29th Bled eConference