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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 13 | Issue 11 | Month- November 2025
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Published Paper Details:
Paper Title
Innovative Web Framework for Cervical Cancer Detection: Harnessing Machine Learning for Improved Diagnosis
Authors
S. Sai Saranya, Dr.P.Nirupama
Keywords
AdaBoost, XGBoost, Stacking Classifier, and Strategic Relapse Models.
Abstract
This study presents a clever online structure intended to distinguish cervical malignant growth by utilizing progressed AI procedures. The structure utilizes a far reaching dataset that envelops factors like socioeconomics, clinical history, sexual action, prophylactic use, and past determinations. It integrates a blend of models including AdaBoost, XGBoost, a stacking classifier, and calculated relapse, all cooperating to improve the accuracy and unwavering quality of the demonstrative interaction. The fundamental point of this system is to help early identification and convenient mediation, which are pivotal for further developing results in cervical malignant growth treatment. Through a top to bottom evaluation and correlation of these models, our exploration exhibits their viability in prescient displaying for cervical disease, denoting a critical commitment to the utilization of AI in medical services.
IJCRT's Publication Details
Unique Identification Number - IJCRT2504365
Paper ID - 281867
Page Number(s) - d89-d95
Pubished in - Volume 13 | Issue 4 | April 2025
DOI (Digital Object Identifier) -
Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
S. Sai Saranya, Dr.P.Nirupama, "Innovative Web Framework for Cervical Cancer Detection: Harnessing Machine Learning for Improved Diagnosis", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 4, pp.d89-d95, April 2025, Available at :http://www.ijcrt.org/papers/IJCRT2504365.pdf
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Volume 13 | Issue 11
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November 2025
Volume 13 | Issue 11
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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