A Novel Breast Cancer Screening System using Logistic Regression
Prasad S Sase
, Debabrata Swain , Shailesh Kumar , Varsha Prasad Sase
Breast cancer disease, Logistic regression, Min-Max scaling, Corelation score, ROC curve
Breast cancer is appearing as one of the most life-threatening illnesses, mostly affecting the females throughout the world. Approximately 67000 female death cases were recoded due to this disease in 2022. Advance diagnosis of the disease, is the only way through which the patient lives can be saved. The disease at its primary stage does not give any symptom about its presence. The proposed approach used logistic regression for the early-stage detection of breast cancer disease. The logistic regression gives a probabilistic output which is mostly used for clinical decision-making process. The breast cancer dataset produced by Wiscon hospital is used for the training and validation of the model. For the feature selection process correlation method is used. The highest accuracy reported by the model is 96.5%.
"A Novel Breast Cancer Screening System using Logistic Regression", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.11, Issue 1, page no.a236-a242, January-2026, Available :https://ijsdr.org/papers/IJSDR2601028.pdf
Volume 11
Issue 1,
January-2026
Pages : a236-a242
Paper Reg. ID: IJSDR_306753
Published Paper Id: IJSDR2601028
Downloads: 000259
Research Area: Science and Technology
Country: Katraj, Pune, India
DOI: https://doi.org/10.56975/ijsdr.v11i1.306753
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
