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  1. 1
    Brain tumor image segmentation using deep learning approach

    Brain tumor image segmentation using deep learning approach by Darshan, Suresh

    Published 2022
    “…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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  2. 2
    Prediction of blood-brain barrier permeability of compounds by machine learning algorithms

    Prediction of blood-brain barrier permeability of compounds by machine learning algorithms by Feng, Tan wei, Raihana Zahirah, Edros, Ngahzaifa, Ab Ghani, Siti Umairah, Mokhtar, Dong, Ruihai

    Published 2024
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  3. 3
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…Furthermore, the low computational burden of MSEDA rendered it a strong alternative to heuristic multi-agent algorithms, which frequently encounter high computational costs with large controller design parameters.…”
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  4. 4
    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm

    Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

    Published 2025
    “…Furthermore, the low computational burden of MSEDA rendered it a strong alternative to heuristic multi-agent algorithms, which frequently encounter high computational costs with large controller design parameters.…”
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  5. 5
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…The use of sensors known as Brain-Computer Interface (BCI) tool can monitor the physical processes and mental states that occur in the human brain. …”
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  6. 6
    Biologically-Inspired Modeling of Filtering Noise in Signal Sound

    Biologically-Inspired Modeling of Filtering Noise in Signal Sound by Hammuzamer , Irwan, Azween, Abdullah

    Published 2009
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  7. 7
    Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling

    Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling by Muhammad Ismaill, Mat Lizah, Nasrul Hadi, Johari, Mohd Jamil, Mohamed Mokhtarudin

    Published 2025
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  8. 8
    Brain Topographic Mapping of Emotions using Computational Cerebellum

    Brain Topographic Mapping of Emotions using Computational Cerebellum by Yaacob, Hamwira Sakti, Kamaruddin, Norhaslinda, Abdul Rahman, Abdul Wahab

    Published 2013
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  9. 9
    A Review: Recent Automatic Algorithms for the Segmentation of Brain Tumor MRI

    A Review: Recent Automatic Algorithms for the Segmentation of Brain Tumor MRI by Rafi, A., Khan, Z., Aslam, F., Jawed, S., Shafique, A., Ali, H.

    Published 2022
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  10. 10
    Brain tumor MRI medical images classification with data augmentation by transfer learning of VGG16

    Brain tumor MRI medical images classification with data augmentation by transfer learning of VGG16 by Ahmed Yahya Al-Galal, Sabaa, Taha Alshaikhli, Imad Fakhri, Abdulrazzaq, M. M., Hassan, Raini

    Published 2021
    “…The ability to estimate conclusions without direct human input in healthcare systems via computer algorithms is known as Artificial intelligence (AI) in healthcare. …”
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  11. 11
    Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device

    Applying SAX-based time series analysis to classify EEG signal using a COTS EEG device by Shanmuga, Pillai A/L Murutha Muthu

    Published 2021
    “…One of the proposals that could help solve this problem is the use of brain-computer interface (BCI)s. Brain-Computer Interface (BCI) can be used as a direct communication path between the brain and an external device. …”
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  12. 12
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  13. 13
    An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa

    An improved diagnostic algorithm based on deep learning for ischemic stroke detection in posterior fossa by Muhd Suberi, Anis Azwani

    Published 2020
    “…Ischemic stroke is triggered by an obstruction in the blood vessel of the brain, preventing the blood to flow to the brain tissues region. …”
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  14. 14
    Alzheimer's diseases detection by using deep learning algorithms: a mini-review

    Alzheimer's diseases detection by using deep learning algorithms: a mini-review by Al-Shoukry, Suhad, Rassem, Taha H., Makbol, Nasrin M.

    Published 2020
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  15. 15
    Classification of multichannel EEG signal by single layer perceptron learning algorithm

    Classification of multichannel EEG signal by single layer perceptron learning algorithm by Hasan, Mohammad Rubaiyat, Ibrahimy, Muhammad Ibn, Motakabber, S. M. A., Shahid, Shahjahan

    Published 2014
    “…Motor imagery (MI) related Electroencephalogram (EEG) signal classification is one of the main challenge in designing a brain computer interface (BCI) system. Single Layer Perceptron Learning (SLPL) algorithm has a very low computational requirement which makes it suitable for online BCI system. …”
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  16. 16
    Alzheimer's diseases detection by using deep learning algorithms: A mini-review

    Alzheimer's diseases detection by using deep learning algorithms: A mini-review by Al-Shoukry, Suhad, Rassem, Taha H., Makbol, Nasrin M.

    Published 2020
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  17. 17
    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar

    Machine learning using robust AI techniques / Prof. Madya Dr. Nordin Abu Bakar by Abu Bakar, Nordin (Prof. Madya Dr.)

    Published 2012
    “…There is a model that studies the social behavior of humans called genetic algorithms (GA). An artificial neural network uses brain as a model to map decisions out of several inputs. …”
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  18. 18
    Alzheimer’s diseases detection by using deep learning algorithms: A mini-review

    Alzheimer’s diseases detection by using deep learning algorithms: A mini-review by Al-Shoukry, Suhad, Rassem, Taha H., Makbol, Nasrin M.

    Published 2020
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  19. 19
    Deep learning for EEG data analysis

    Deep learning for EEG data analysis by Cheah, Kit Hwa

    Published 2018
    “…Electroencephalogram (EEG) is a multi-dimensional time-series brain signal that is highly information packed. While an EEG has high potential to serve in medicine (e.g. disease diagnosis, prognosis, pre-disease risk identification), psycho-physiology (e.g. mood classification, stress monitoring, alertness monitoring, sleep stage monitoring), brain-computer interface application (e.g. thought typing, prosthesis control), and many other areas, the classical design of EEG feature extraction algorithms and EEG classifiers is time-consuming and challenging to fully tap into the vast data embedded in the EEG. …”
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  20. 20
    Biologically-Inspired Abstraction Model to Analyze Sound Signal

    Biologically-Inspired Abstraction Model to Analyze Sound Signal by Hammuzamer Irwan , Hamzah, Azween, Abdullah

    Published 2008
    “…Subsequently, the brain is capable to recognize and learn the sound signal. …”
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