Paper Contents
Abstract
Brain tumors are a significant health concern globally, with early and accurate detection being critical for effective treatment and improved patient outcomes. This paper presents an innovative approach for brain tumor detection and classification using a two-level diagnosis system. The proposed system combines advanced medical imaging techniques with artificial intelligence algorithms to enhance the accuracy and efficiency of brain tumor diagnosis. Furthermore, the proposed system incorporates an expert system that integrates medical knowledge and decision-making rules. The expert system refines the diagnosis results by considering additional clinical parameters, patient history, and expert opinions, ensuring a comprehensive and accurate diagnosis. This research contributes significantly to the field of medical imaging and artificial intelligence, offering a robust and reliable solution for brain tumor detection and classification. The proposed system has the potential to revolutionize clinical practices, leading to early diagnosis, personalized treatment plans, and ultimately, improved outcomes for patients with brain tumors.
Copyright
Copyright © 2023 Prof. Pramod Patil. This is an open access article distributed under the Creative Commons Attribution License.
