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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
Predicting Diabetes Risk in Pima Indian Women Using Deep Learning Model
Authors
Palak Majevadiya, Nidhi Joshi
Keywords
Diabetes,LSTM,Deep Learning,Soft Max
Abstract
Diabetes mellitus remains a pervasive public health issue, particularly among certain ethnic groups such as the Pima Indian community. This study leverages deep learning methodologies to forecast the risk of Type 2 diabetes in Pima Indian women using the well-established Pima Indian Diabetes dataset. Employing Artificial Neural Networks (ANNs), including multilayer perception architectures, the model identifies intricate, nonlinear patterns in clinical data such as glucose levels, BMI, and age. Results indicate that the deep learning model achieves superior accuracy and robustness compared to traditional machine learning methods, underscoring its potential as a viable tool for early detection and personalized intervention strategies in diabetes.
IJCRT's Publication Details
Unique Identification Number - IJCRT2504814
Paper ID - 282710
Page Number(s) - g909-g916
Pubished in - Volume 13 | Issue 4 | April 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Palak Majevadiya, Nidhi Joshi, "Predicting Diabetes Risk in Pima Indian Women Using Deep Learning Model", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 4, pp.g909-g916, April 2025, Available at :http://www.ijcrt.org/papers/IJCRT2504814.pdf
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Volume 14 | Issue 2
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Volume 14 | Issue 2
Last Date :
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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