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Title: :  INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION
PaperId: :  21748
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 9 Issue 5 2023
DUI:    16.0415/IJARIIE-21748
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Maadhini NarayanaKumarBannari Amman institute of technology
Esakki Madura E Bannari Amman institute of technology

Abstract

Computer Engineering
Polycystic Ovary Syndrome; Machine Learning; Webapplication ;Health;
This paper introduces an innovative approach to Polycystic Ovary Syndrome (PCOS) detection through the development of a web-based application. PCOS is a prevalent and complex endocrine disorder affecting millions of individuals worldwide. Our solution leverages modern tools, including Streamlit, for effective web app development. It incorporates machine learning algorithms to enable early and accurate PCOS prediction based on user-provided data and genetic features.This project encompasses data collection, preprocessing, and model training, employing Bayesian optimization and stacked deep ensemble learning techniques. By combining these advanced methodologies, our web application can enhance the prediction of PCOS, assisting individuals in early diagnosis and treatment. This novel tool's effectiveness is evaluated using a diverse dataset, showcasing its potential to revolutionize PCOS diagnosis and healthcare accessibility.The study demonstrates the power of modern technology, particularly Streamlit, in developing user-friendly and efficient healthcare tools. It highlights the significance of early PCOS detection and the role of machine learning in advancing medical diagnostics. The application's potential impact on improving healthcare outcomes and reducing PCOS-related health costs is substantial, signifying a promising endeavor at the intersection of healthcare and technology.

Citations

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IJARIIE Maadhini NarayanaKumar, and Esakki Madura E . "INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION" International Journal Of Advance Research And Innovative Ideas In Education Volume 9 Issue 5 2023 Page 1530-1543
MLA Maadhini NarayanaKumar, and Esakki Madura E . "INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION." International Journal Of Advance Research And Innovative Ideas In Education 9.5(2023) : 1530-1543.
APA Maadhini NarayanaKumar, & Esakki Madura E . (2023). INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION. International Journal Of Advance Research And Innovative Ideas In Education, 9(5), 1530-1543.
Chicago Maadhini NarayanaKumar, and Esakki Madura E . "INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION." International Journal Of Advance Research And Innovative Ideas In Education 9, no. 5 (2023) : 1530-1543.
Oxford Maadhini NarayanaKumar, and Esakki Madura E . 'INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION', International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, 2023, p. 1530-1543. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/INTRODUCTION_TO_POLYCYSTIC_OVARY_SYNDROME_DETECTION_MACHINE_LEARNING_MODEL_BASED_ON_OPTIMIZED_FEATURE_SELECTION_ijariie21748.pdf (Accessed : ).
Harvard Maadhini NarayanaKumar, and Esakki Madura E . (2023) 'INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION', International Journal Of Advance Research And Innovative Ideas In Education, 9(5), pp. 1530-1543IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/INTRODUCTION_TO_POLYCYSTIC_OVARY_SYNDROME_DETECTION_MACHINE_LEARNING_MODEL_BASED_ON_OPTIMIZED_FEATURE_SELECTION_ijariie21748.pdf (Accessed : )
IEEE Maadhini NarayanaKumar, and Esakki Madura E , "INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION," International Journal Of Advance Research And Innovative Ideas In Education, vol. 9, no. 5, pp. 1530-1543, Sep-Oct 2023. [Online]. Available: https://ijariie.com/AdminUploadPdf/INTRODUCTION_TO_POLYCYSTIC_OVARY_SYNDROME_DETECTION_MACHINE_LEARNING_MODEL_BASED_ON_OPTIMIZED_FEATURE_SELECTION_ijariie21748.pdf [Accessed : ].
Turabian Maadhini NarayanaKumar, and Esakki Madura E . "INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 9 number 5 ().
Vancouver Maadhini NarayanaKumar, and Esakki Madura E . INTRODUCTION TO POLYCYSTIC OVARY SYNDROME DETECTION MACHINE LEARNING MODEL BASED ON OPTIMIZED FEATURE SELECTION. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2023 [Cited : ]; 9(5) : 1530-1543. Available from: https://ijariie.com/AdminUploadPdf/INTRODUCTION_TO_POLYCYSTIC_OVARY_SYNDROME_DETECTION_MACHINE_LEARNING_MODEL_BASED_ON_OPTIMIZED_FEATURE_SELECTION_ijariie21748.pdf
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