Empowering Precision Medicine: AI-Driven Schizophrenia Diagnosis via EEG Signals: A Comprehensive Review from 2002-2023

no code implementations • 14 Sep 2023 • Mahboobeh Jafari, Delaram Sadeghi, Afshin Shoeibi, Hamid Alinejad-Rokny, Amin Beheshti, David López García, Zhaolin Chen, U. Rajendra Acharya, Juan M. Gorriz

Subsequently, review papers in this field are discussed, followed by an introduction to the AI methods employed for SZ diagnosis and a summary of relevant papers presented in tabular form.

EEG

Revolutionizing Genomics with Reinforcement Learning Techniques

no code implementations • 26 Feb 2023 • Mohsen Karami, Roohallah Alizadehsani, Khadijeh, Jahanian, Ahmadreza Argha, Iman Dehzangi, Hamid Alinejad-Rokny

In recent years, Reinforcement Learning (RL) has emerged as a powerful tool for solving a wide range of problems, including decision-making and genomics.

Decision Making reinforcement-learning +1

HYDRA-HGR: A Hybrid Transformer-based Architecture for Fusion of Macroscopic and Microscopic Neural Drive Information

no code implementations • 27 Oct 2022 • Mansooreh Montazerin, Elahe Rahimian, Farnoosh Naderkhani, S. Farokh Atashzar, Hamid Alinejad-Rokny, Arash Mohammadi

At the same time, advancements in acquisition of High-Density sEMG signals (HD-sEMG) have resulted in a surge of significant interest on sEMG decomposition techniques to extract microscopic neural drive information.

Hand Gesture Recognition Hand-Gesture Recognition

Deep Learning in Spatially Resolved Transcriptomics: A Comprehensive Technical View

no code implementations • 10 Oct 2022 • Roxana Zahedi Nasab, Mohammad Reza Eftekhariyan Ghamsari, Ahmadreza Argha, Callum Macphillamy, Amin Beheshti, Roohallah Alizadehsani, Nigel H. Lovell, Mohammad Lotfollahi, Hamid Alinejad-Rokny

In this paper, we provide a comprehensive overview of these deep learning methods, including their strengths and limitations.

Clustering