Machine Learning and Deep Learning Approaches for Brain Disease Diagnosis: Principles and Recent Advances
importance 7/10
ai assisted
Brain Tumor Detection and Classification neurology diagnostics stage: research
Problem
Early detection of variable brain diseases (Alzheimer's, brain tumor, epilepsy, Parkinson's) remains an open diagnostic challenge.
Why it matters
Early brain disease detection can significantly improve treatment chances.
What the AI did
A review of 147 recent articles surveying machine learning and deep learning approaches for detecting four brain diseases.
Results
not stated in source
Impact
Review claims AI improves detection accuracy but cites no concrete metrics.
Record
| Venue | IEEE Access |
|---|---|
| Published | 2021 |
| Work type | article |
| Authors | Protima Khan, Md. Fazlul Kader, S. M. Riazul Islam, Aisha B Rahman, Md. Shahriar Kamal, Masbah Uddin Toha, Kyung Sup Kwak |
| Citations | 293 (OpenAlex, at import time) |
| References | 188 |
| Model or method | not stated in source |
| Organization | not stated in source |
| Primary source | https://doi.org/10.1109/access.2021.3062484 |
| Open access | gold |
| Keywords | machine learning, deep learning, brain disease, diagnosis, Alzheimer's, review |
Importance rating
7
significant — thousands to millions affected
Early detection of Alzheimer's, brain tumor, epilepsy and Parkinson's is framed as making a huge difference to cures, but the abstract gives no numbers on affected populations or accuracy gains.