NSGA‐II‐XGB: Meta‐heuristic feature selection with XGBoost framework for diabetes prediction-Reference-Cited by-同舟云学术

NSGA‐II‐XGB: Meta‐heuristic feature selection with XGBoost framework for diabetes prediction

Published:2022-07-27 Issue:21 Volume:34 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Gupta Aditya¹^ORCID,Rajput Ishwari Singh²,Gunjan ¹,Jain Vibha³^ORCID,Chaurasia Soni¹

Affiliation:

1. Department of Computer Science and Engineering SRM University, Delhi‐NCR Sonipat India

2. Department of Computer Science and Engineering Graphic Era Hill University Haldwani Uttarakhand India

3. Department of Computer Science and Engineering Netaji Subhas University of Technology New Delhi India

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.7123

Reference41 articles.

1. A critical review of national diabetes prevention and control programs in 12 countries in Middle East

2. IDF diabetes atlas: global, regional and country‐level diabetes prevalence estimates for 2021 and projections for 2045;Sun H;Diabetes Res Clin Pract,2021

3. Global Prevalence of Diabetic Retinopathy and Projection of Burden through 2045

4. PatiA ParhiM PattanayakBK.IADP: an integrated approach for diabetes prediction using classification techniques;2022:287‐298; Springer.

5. Economic burden of diabetic patients in India: A review

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