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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Volume 10 | Issue 12
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19459
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
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| Paper Title: | DEEP LEARNING MODELS ON EARLY DETECTION OF DIABETES MELLITUS |
| Authors Name: | M Ruthika , Mooli Sai Manogna , Nachukuri Pranathi , Kanala Mamatha , K Pavani, Mr. A Venkatesan, Dr. R Karunia Krishnapriya |
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IJRTI_202289
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| Published Paper Id: | IJRTI2504104 |
| Published In: | Volume 10 Issue 4, April-2025 |
| DOI: | |
| Abstract: | In order to avoid serious complications, diabetes mellitus (DM), a chronic illness, must be identified early. The usefulness of feature transformation methods and machine learning models-more especially, CatBoost and Artificial Neural Networks (ANN)-in early diabetes prediction is assessed in this study. To improve model performance, feature transformation techniques such as Principal Component Analysis (PCA), normalization, and standardization were used. ANN, a deep learning technique that can identify intricate patterns in medical data, was contrasted with the CatBoost algorithm, which is well-known for its effectiveness in managing categorical data and minimizing overfitting. To evaluate the predictive power of these models, evaluation criteria such as accuracy, precision, recall, and F1-score were used. |
| Keywords: | Deep Learning, Diabetes Prediction, Neural Networks, Clinical Decision Support, Predictive Modeling. Health Informatics, Diabetes Dataset, Data Preprocessing |
| Cite Article: | "DEEP LEARNING MODELS ON EARLY DETECTION OF DIABETES MELLITUS ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.b18-b24, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504104.pdf |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2504104
Registration ID:202289
Published In: Volume 10 Issue 4, April-2025
DOI (Digital Object Identifier):
Page No: b18-b24 Country: Chittoor, Andhra Pradesh, India Research Area: Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2504104 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2504104 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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