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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| 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
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| Series: | Neutrosophic Sets and Systems |
| Subjects: | |
| Online Access: | https://fs.unm.edu/NSS/48BreastCancer.pdf |
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