| Issue |
BIO Web Conf.
Volume 204, 2025
International Conference on Advancing Science and Technologies in Health Science (IEM-HEALS 2025)
|
|
|---|---|---|
| Article Number | 01024 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/bioconf/202520401024 | |
| Published online | 12 December 2025 | |
Artificial Intelligence Perspective on MRI-Driven Computer-Aided Diagnosis and Prognosis of the Brain: A Systematic Review
1 Department of Electronics and Communication Engineering, United University, Prayagraj, India
2 Department of Electronics and Communication Engineering, United College of Engineering and Research, Prayagraj, India
3 Department of Computer Science Engineering, United University, Prayagraj, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Recently, the involvement of Artificial Intelligence (AI) has empowered CAD in the diagnosis of brain illnesses. Due to the escalating incidence of brain diseases, there has been a low awareness among the population, and thus, the need for AI emerges to fulfill the requirements in this domain. Artificial intelligence (AI), encompassing various subfields of computer science, is essential for analyzing medical data and extracting datasets, which augment human intelligence. Specifically, in the brain investigation domain, several productive measures have been taken and executed remarkably in the disciplines of diagnosis, framing, and outcomes. In this study, we outline different artificial intelligence techniques used in diagnosing the brain sphere. Eventually, we will notice that AI has made it possible to revamp medical images in neuroscience applications. This study directs the current revolutionary trends as well as considers future diagnostic research that is based on Computer-Aided Diagnose and Computer-Aided Prognosis for the explicit detection of patients with brain disorders.
Key words: Artificial Intelligence (AI) / Magnetic Resonance Imaging (MRI) / Computed Tomography (CT) / Machine Learning (ML) / Computer-Aided Diagnostics (CAD)
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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