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Year : 2021  |  Volume : 11  |  Issue : 2  |  Page : 148-153

Data Analysis of Autism Disorder and Micronutrition using PubMed Abstracts

Department of Family Medicine, Dongguk University College of Medicine, Gyeongju, South Korea

Correspondence Address:
Hwee-Soo Jeong
Department of Family Medicine, Dongguk University College of Medicine, Dongda-ro 123, Gyeongjusi, Gyeongsangbuk-do 38066
South Korea
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijnpnd.ijnpnd_104_20

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Aim: This study was conducted to identify the notable nutrients mentioned in abstracts of articles about autism disorder using the big data analysis method. Methods and Materials: Abstracts of articles on nutrients related to autism disorder were extracted from MEDLINE using PubMed. Text mining was performed to extract nutrient-related words from collected research abstracts. Network analysis was performed using nutrients keywords and showed more than 100 occurrences among extracted words. Results: As a result of text mining 932 abstracts, the top 10 Nutrients that appeared more than 100 times were vitamin D omega 3, zinc, iron, copper, vitamin B6, vitamin B12, folate, calcium, and probiotics, in decreasing order. Folate and copper were central nutrients in the central analysis of the network made by 10 nutrients. Grouping the 10 nutrients showed folic acid, vitamin B6, vitamin B12, calcium, iron, zinc, copper, omega 3 in group 1, probiotics in group 2, and vitamin D in group 3. Conclusions: A variety of nutrients, including vitamin D, folate, and copper, were found to be related to autism disorder by big data analysis of abstracts of nutrition research studies related to this disorder.

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