Prediction of brain stroke using machine learning algorithms and deep neural network techniques S Rahman, M Hasan, AK Sarkar European Journal of Electrical Engineering and Computer Science 7 (1), 23-30, 2023 | 27 | 2023 |
Classification of Parkinson’s disease using speech signal with machine learning and deep learning approaches S Rahman, M Hasan, AK Sarkar, F Khan European Journal of Electrical Engineering and Computer Science 7 (2), 20-27, 2023 | 10 | 2023 |
Machine Learning and Deep Neural Network Techniques for Heart Disease Prediction S Rahman, MM Hasan, AK Sarkar 2022 25th International Conference on Computer and Information Technology …, 2022 | 5 | 2022 |
A Novel Artificial Intelligence (AI) Method to Classify and Predict the Progression of Alzheimers Disease MM Hasan, S Rahman, H Parmar, S Chowdhury bioRxiv, 2024.06. 03.597177, 2024 | | 2024 |
Different Methods of EEG Signal Analysis Using Power Spectral Density, ChronoNet and ResNest MM Hasan, S Rahman, A Sarkar, F Khan, A Seum European Journal of Electrical Engineering and Computer Science 7 (5), 20-27, 2023 | | 2023 |
Comparative Analysis of Different Approaches For Detecting Epilepsy S Rahman, AK Sarkar 2022 International Conference on Recent Progresses in Science, Engineering …, 2022 | | 2022 |
Methods for Detecting Epilepsy: A Comparative Analysis on Improved Deep Learning Algorithms S Rahman, MM Hasan, AK Sarkar 2022 12th International Conference on Electrical and Computer Engineering …, 2022 | | 2022 |
Comparative Analysis of Three Different Microstrip Patch Antennas on the Rat Model S Rahman, MK Hosain, AK Sarkar, MM Hasan 2017 2nd International Conference on Electrical & Electronic Engineering …, 2017 | | 2017 |
Biocompatibility analysis of a battery less back-mountable DBS device S Rahman, F Khushi, K Hosain 2016 2nd International Conference on Electrical, Computer …, 2016 | | 2016 |
Deep Learning and Multiclass Machine Learning Classifier Approach for Predicting Primary Tumors MM Hasan, S Rahman, AK Sarkar IJFMR-International Journal For Multidisciplinary Research 5 (1), 0 | | |