Please use this identifier to cite or link to this item: https://hdl.handle.net/10321/4294
Title: Artificial intelligence–based neural network for the diagnosis of diabetes and COVID
Authors: Roland, Gilbert 
Kumar, Navin 
Gururaj, Bharathi 
Richa, Richa 
Bobade, Sunil Devidas 
Lourens, Melanie Elizabeth
Keywords: Diabetes mellitus;Neural network;Artificial intelligence
Issue Date: 1-Jul-2022
Publisher: Universidad Tecnica de Manabi
Source: Roland, G. et al. 2022. Artificial intelligence–based neural network for the diagnosis of diabetes and COVID. International journal of health sciences. Special Issue 1: 13945-13959. doi:10.53730/ijhs.v6ns1.8606
Journal: International Journal of Health Sciences; Vol. Special Issue 1 
Abstract: 
In many nations, the prevalence of diabetes is rising, and its impact on national health cannot be overlooked. Smart medicine is a medical concept in which technology is used to aid in disease detection and treatment. The objective of this study is to take a gander at the information and look at changed diabetic mellitus forecasting algorithms. According to rising dismalness as of late, the quantity of diabetic patients worldwide will arrive at 642 million out of 2040, suggesting that one out of each 10persons would be affected. This worrisome figure, without a question, demands immediate attention. AI has been applied to an assortment of aspects of clinical wellbeing as a result of its rapid progress. To predict diabetes mellitus in this review, we utilized a choice tree, an arbitrary timberland, and a neural organization.
URI: https://hdl.handle.net/10321/4294
ISSN: 2550-6978
2550-696X (Online)
DOI: 10.53730/ijhs.v6ns1.8606
Appears in Collections:Theses and dissertations (Management Sciences)

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