Early Diagnosis of Brain Tumor Using AI and Mathematical Modeling

Early Diagnosis of Brain Tumor Using AI and Mathematical Modeling

Tanisha Kumar1*, Suryansh Ahlawat2*, Anupam Swami3, Ajay Singh Yadav4

1Student, B. Tech (Computer Science and Engineering-AIML), SRM Institute of Science and Technology Delhi-NCR Campus, Ghaziabad, U.P

2Student B. Tech (Computer Science and Engineering-Data Science), SRM Institute of Science and Technology Delhi-NCR Campus, Ghaziabad, U.P

3Department of Mathematics, Km. Mayawati Government Girls P.G. College, Badalpur, Gautam Buddha Nagar (U.P.)

4Department of Mathematics, SRM Institute of Science and Technology Delhi-NCR Campus, Ghaziabad, U.P

*Corresponding Author Email:tanishakumar26@gmail.com, sa9209@srmist.edu.in

Abstract:

Timely detection of Brain Tumors is crucial for improving patient outcomes and reducing mortality rates. This study explores the significance of early diagnosis and investigates the role of various diagnostic methods. Leveraging advancements in medical imaging, including MRI, CT scans, and PET scans, alongside blood tests measuring biomarkers such as glial fibrillary acidic protein (GFAP) and neuron-specific enolase (NSE), facilitates early detection of Brain Tumors. Furthermore, emerging technologies like artificial intelligence algorithms enhance the accuracy and efficiency of diagnosis by analyzing imaging data and identifying subtle abnormalities. Early detection not only offers patients more treatment options but also improves their prognosis. Therefore, it is crucial to raise awareness about the importance of regular screenings and symptom awareness to ensure early detection and timely intervention for Brain Tumors.

Keywords: Brain tumor, Early detection, Artificial intelligence, Mathematical modeling, Medical imaging, Mammography, liver MRI, Machine learning, Deep learning, Screening strategies.