Abstract
Brain tumor detection is a critical application in the field of medical imaging, aimed at aiding healthcare professionals in the early and accurate diagnosis of brain tumors. This project leverages machine learning and deep learning techniques in Python to develop a robust and reliable brain tumor detection system. The system undergoes sensitivity and uncertainty analyses to assess its performance under diverse data conditions and to quantify the impact of variations and uncertainties on the model's accuracy. By systematically evaluating the model's sensitivity to various factors and understanding the sources of uncertainty, this project contributes to enhancing the system's reliability and readiness for clinical use. The findings provide insights into optimization and robustness enhancements, ultimately facilitating better patient care and outcomes in the diagnosis of brain tumors.
Citations
IRE Journals:
Vishwakarma Hemant Dinesh , Navpreetkaur Dusanje , Poonam Jain , Santosh Singh
"Brain Tumor Detection Using Python" Iconic Research And Engineering Journals Volume 7 Issue 8 2024 Page 125-130
IEEE:
Vishwakarma Hemant Dinesh , Navpreetkaur Dusanje , Poonam Jain , Santosh Singh
"Brain Tumor Detection Using Python" Iconic Research And Engineering Journals, 7(8)
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