Precision Medicine in Neurology: In-depth Investigation and Revolutionizing Brain Tumor Detection and Treatment

Penumudi, Yamuna Sai (2024) Precision Medicine in Neurology: In-depth Investigation and Revolutionizing Brain Tumor Detection and Treatment. Masters thesis, Dublin, National College of Ireland.

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Abstract

Brain tumor detection and classification are critical areas in the area of neuroscience as fast diagnosis and treatment planning is possible for patients with neurological disease. This thesis is devoted to the thorough examination of the recent deep learning approaches for brain tumor detection and segmentation. Our research concerns the implementation of a robust strategy based on the advanced model, with EfficientNetB3 architecture as a backend and the dataset of MRI images, which was retrieved from authoritative sources. The ultimate target is creating a reliable and precise model which will be efficient in separating various brain tumor types form the healthy brain tissue. As a result of a rigorous methodology that involves data preprocessing, modeling, training and evaluation, we have demonstrated the benefit of our approach. In addition, we will underscore the practicality of our model in real-world clinical settings, keeping in mind to as well contribute to the progress of precision treating neurological disorders. Our study stresses a lot on the aspects of transparency and reproducibility which are made clear by highlighting the model architecture, dataset specifications and also the evaluation metrics used. Through a comprehensive assessment which involves a variety of performance parameters like the accuracy, precision, recall, and F1-score, we prove the high performance and persistent nature of our proposed ideology. Moreover, the talking point is interpretation and easy to understand. Therefore, the area of discussion includes a detailed explanation of the results which includes confusions matrix and accuracy reports. Overall, our study showed that the method we used made significant contributions to the field of neurology by taking the industry standards for brain tumor detection and classification up a notch. It is our goal to capitalize on deep learning models and the strict data science sensibility in order to aid the clinicians and researchers in the process of providing the best patient care and to contribute greatly in the precision medicine care goals.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Shahid, Abdul UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry R Medicine > Healthcare Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	05 Jun 2025 15:07
Last Modified:	05 Jun 2025 15:07
URI:	https://norma.ncirl.ie/id/eprint/7768

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