Repository logo
 

Artificial intelligence–based neural network for the diagnosis of diabetes and COVID

Thumbnail Image

Date

2022-07-01

Authors

Roland, Gilbert
Kumar, Navin
Gururaj, Bharathi
Richa, Richa
Bobade, Sunil Devidas
Lourens, Melanie Elizabeth

Journal Title

Journal ISSN

Volume Title

Publisher

Universidad Tecnica de Manabi

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.

Description

Keywords

Diabetes mellitus, Neural network, Artificial intelligence

Citation

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

DOI

10.53730/ijhs.v6ns1.8606

Endorsement

Review

Supplemented By

Referenced By