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Using machine learning to address data accuracy and information integrity in digital health delivery

Version 2 2024-06-04, 00:32
Version 1 2017-05-09, 14:26
conference contribution
posted on 2024-06-04, 00:32 authored by ZZ 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

Event

Bled. eConference (29th : 2016 : Bled, Slovenia)

Publisher

Association for Information Systems

Place of publication

Atlanta, Ga.