Machine Learning Based Breast Cancer Detection

Milan Patel, Ashphak Khan, Tejas Patel, Nikhil Patel and Hiren Chaudhari
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Milan Patel: Computer, D.N.Patel College Of Engineering
Ashphak Khan: Computer, D.N.Patel College Of Engineering
Tejas Patel: Computer, D.N.Patel College Of Engineering
Nikhil Patel: Computer, D.N.Patel College Of Engineering
Hiren Chaudhari: Computer, D.N.Patel College Of Engineering

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 5, 1114-1118

Abstract: In this study, a novel ultra-wideband (UWB) radar-based method for early, non-invasive breast cancer diagnosis is presented. The system uses a curved seventh derivative Gaussian UWB pulse that is filtered by a sharp transition bandpass FIR filter in both monostatic and bistatic radar configurations. The pulse shape enhances radiation power, spectrum efficiency, and FCC-compliant safety. Tumors are located and detected using Specific Absorption Rate (SAR) measurement and backscattered signal processing. Results from experiments and simulations confirm that the system can accurately identify cancers.

Date: 2025
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