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Evaluation of users' level of satisfaction for an artificial intelligence-based diagnostic program in pediatric rare genetic diseases

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Abstract
The artificial intelligence (AI)-based genetic diagnostic program has been applied to genome sequencing to facilitate the diagnostic process. The objective of the current study was to evaluate the experience and level of satisfaction of participants using an AI-based diagnostic program for rare pediatric genetic diseases. The patients with neurodevelopmental disorders or hearing impairments, their guardians, and their physicians from 16 tertiary general hospitals were enrolled. The study period was from April 2020 to March 2021. A survey was designed to assess their experience and level of satisfaction. A total of 30 physicians and 243 patients and guardians (199 neurodevelopmental disorders and 44 hearing impairments) completed the survey. DNA samples of the subjects were collected through buccal swabs or blood collection: 211 subjects (86.8%) through buccal swab and 29 subjects (11.9%) through blood collection. Average turnaround time for result receipt was 57.54 ± 32.42 days. For the sampling method, 193 patients and guardians (81.1%) and 28 physicians (93.3%) preferred buccal swab. The level of satisfaction of the 2 groups participating in the AI-based diagnostic program was 8.31 ± 1.71 out of 10 in the patient and guardian group and 8.42 ± 1.23 in the physician group. Clinicians, patients, and guardians are satisfied with the AI-based diagnostic program in general. With an increase in AI-based precision medicine solutions, the evaluation of the user's satisfaction with appropriate provision will help improve personal health care.
Author(s)
In Hee ChoiGo Hun SeoJeongYun ParkYoon-Myung KimChong Kun CheonYoo-Mi KimArum OhJung Hye ByeonEungu KangYoung-Lim ShinJi Eun LeeSu Jin KimHee Joon YuWoo Jin KimByung Yoon ChoiBong Jik KimYoung Ho KimGi Jung ImHyo-Jeong LeeHyun Ji KimSe-Hee HanBeom Hee LeeBaik-Lin Eun
Issued Date
2022
Type
Article
Keyword
artificial intelligence-based diagnostic programbuccal swabmedical data analysis diagnostic intelligent softwarerare diseasewhole-exome sequencing
DOI
10.1097/MD.0000000000029424
URI
https://oak.ulsan.ac.kr/handle/2021.oak/13681
Publisher
MEDICINE
Language
영어
ISSN
0025-7974
Citation Volume
101
Citation Number
28
Citation Start Page
1
Citation End Page
7
Appears in Collections:
Medicine > Nursing
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