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Using Artificial Intelligence in Everyday Management of Diabetes Type 1 : A Cross Sectional Study of the Role of AI for Individual Patients

Diabetes type 1 is an autoimmune, incurable disease which requires careful monitoring and treatment to not result in life threatening complications. Managing the disease is to a great extent made by the patients themselves, implying the disease needs to be constantly taken into consideration when doing even the most simple and regular everyday tasks and activities.This study aims to examine the use of AI in everyday treatment for patients with diabetes type 1. The study investigated what areas AI is already used in diabetes care management, and where there is room for development. The purpose is to give an indication of what role AI has and potentially can have in making the life for patients with diabetes type 1 easier. The research was conducted by a combined literature review and a cross sectional multiple case-study, with semi-structured interviews with people diagnosed with diabetes type 1. The gathered data were analyzed in relation to the triangle of diabetes management and technology acceptance model 2. The first indicates what factors are of highest relevance to not create dangerous situations for a diabetic, and the second relates to whether users would accept the use of a complex technology. The result suggested wide current and further potential use of AI in creating functionality in treatment and everyday management of the disease. Further, it became evident that technological tools simplify the lives of diabetics but there are several areas where AI could be further implemented in order to improve it even further.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-467030
Date January 2022
CreatorsLivman, Sofia, Josefsson, Benjamin
PublisherUppsala universitet, Institutionen för informatik och media
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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