Advancing Breast Cancer Diagnosis: A Comprehensive Machine Learning Approach for Predicting Malignant and Benign Cases with Precision and Insight in a Neutrosophic Environment using Neutrosophic Numbers

Breast cancer is still among the deadliest diseases globally, and its detection in an early stage still represents a big challenge in medical diagnostics. This research suggests a complete machine learning framework to predict the probability of benign and malignant breast cancer cases with improved...

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Bibliographic Details
Main Authors: Nihar Ranjan Panda, R. Rajalakshmi, Surapati Pramanik, Mana Donganont, Prasanta Kumar Raut
Format: Article
Language:English
Published: University of New Mexico 2025-07-01
Series:Neutrosophic Sets and Systems
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Online Access:https://fs.unm.edu/NSS/48BreastCancer.pdf
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