no code implementations • 9 Apr 2024 • Milad Yousefi, Shadi Farabi Maleki, Ali Jafarizadeh, Mahya Ahmadpour Youshanlui, Aida Jafari, Siamak Pedrammehr, Roohallah Alizadehsani, Ryszard Tadeusiewicz, Pawel Plawiak
The application of AI and radiomics to thyroid cancer diagnosis is examined in this review.
no code implementations • 28 Feb 2024 • Yasin Sadeghi Bazargani, Majid Mirzaei, Navid Sobhi, Mirsaeed Abdollahi, Ali Jafarizadeh, Siamak Pedrammehr, Roohallah Alizadehsani, Ru San Tan, Sheikh Mohammed Shariful Islam, U. Rajendra Acharya
With the ability to evaluate the patient's health status vis a vis DM complication as well as risk prognostication of future cardiovascular complications, AI-assisted retinal image analysis has the potential to become a central tool for modern personalized medicine in patients with DM.
no code implementations • 15 Feb 2024 • Ali Jafarizadeh, Shadi Farabi Maleki, Parnia Pouya, Navid Sobhi, Mirsaeed Abdollahi, Siamak Pedrammehr, Chee Peng Lim, Houshyar Asadi, Roohallah Alizadehsani, Ru-San Tan, Sheikh Mohammad Shariful Islam, U. Rajendra Acharya
Retinopathy of prematurity (ROP) is a severe condition affecting premature infants, leading to abnormal retinal blood vessel growth, retinal detachment, and potential blindness.
no code implementations • 14 Dec 2023 • Danial Sharifrazi, Nouman Javed, Roohallah Alizadehsani, Prasad N. Paradkar, U. Rajendra Acharya, Asim Bhatti
To characterize this mosquito neural activity, it is essential to classify the generated electrical spikes.
no code implementations • 18 Nov 2023 • Elham Nasarian, Roohallah Alizadehsani, U. Rajendra Acharya, Kwok-Leung Tsui
It breaks down the interpretability process into data pre-processing, model selection, and post-processing, aiming to foster a comprehensive understanding of the crucial role of a robust interpretability approach in healthcare and to guide future research in this area.
no code implementations • 12 Nov 2023 • Khadijeh, Jahanian, Elnaz Shalbafian, Morteza Saberi, Roohallah Alizadehsani, Iman Dehzangi
Our analyses reveal that either APOBEC3 enzymes are not active against HBV, or the induction of G-to-A mutations by these enzymes is not sequence context-dependent in the HBV genome.
no code implementations • 11 Nov 2023 • Mirsaeed Abdollahi, Ali Jafarizadeh, Amirhosein Ghafouri Asbagh, Navid Sobhi, Keysan Pourmoghtader, Siamak Pedrammehr, Houshyar Asadi, Roohallah Alizadehsani, Ru-San Tan, U. Rajendra Acharya
This paper provides an overview of the recent developments and difficulties in using artificial intelligence and retinal imaging to diagnose cardiovascular diseases.
no code implementations • 22 Sep 2023 • Saeid Nahavandi, Roohallah Alizadehsani, Darius Nahavandi, Chee Peng Lim, Kevin Kelly, Fernando Bello
Automated industries lead to high quality production, lower manufacturing cost and better utilization of human resources.
no code implementations • 21 Sep 2023 • Roohallah Alizadehsani, Solomon Sunday Oyelere, Sadiq Hussain, Rene Ripardo Calixto, Victor Hugo C. de Albuquerque, Mohamad Roshanzamir, Mohamed Rahouti, Senthil Kumar Jagatheesaperumal
This review article provides a comprehensive overview of the current state-of-the-art in XAI for drug discovery, including various XAI methods, their application in drug discovery, and the challenges and limitations of XAI techniques in drug discovery.
no code implementations • 29 Aug 2023 • Elham Nasarian, Danial Sharifrazi, Saman Mohsenirad, Kwok Tsui, Roohallah Alizadehsani
The accuracy of coronary artery disease (CAD) diagnosis is dependent on a variety of factors, including demographic, symptom, and medical examination, ECG, and echocardiography data, among others.
1 code implementation • 27 Apr 2023 • H M Dipu Kabir, Subrota Kumar Mondal, Sadia Khanam, Abbas Khosravi, Shafin Rahman, Mohammad Reza Chalak Qazani, Roohallah Alizadehsani, Houshyar Asadi, Shady Mohamed, Saeid Nahavandi, U Rajendra Acharya
In the proposed NN training method for UQ, first, we train a shallow NN for the point prediction.
no code implementations • 4 Apr 2023 • Zahra Sadeghi, Roohallah Alizadehsani, Mehmet Akif Cifci, Samina Kausar, Rizwan Rehman, Priyakshi Mahanta, Pranjal Kumar Bora, Ammar Almasri, Rami S. Alkhawaldeh, Sadiq Hussain, Bilal Alatas, Afshin Shoeibi, Hossein Moosaei, Milan Hladik, Saeid Nahavandi, Panos M. Pardalos
This paper presents a systematic review of XAI aspects and challenges in the healthcare domain.
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.
no code implementations • 7 Feb 2023 • Seyedeh Sedigheh Abedini, Shiva Akhavan, Julian Heng, Roohallah Alizadehsani, Iman Dehzangi, Denis C. Bauer, Hamid Rokny
Of the remaining 30 regions, we identify 24 regions containing at least one protein-coding genes with brain-enriched expression and nervous system phenotype in mouse mutant and one lncRNAs with both brain-enriched expression and upregulation in iPSC to neuron differentiation.
no code implementations • 4 Nov 2022 • Javad Hassannataj Joloudari, Sadiq Hussain, Mohammad Ali Nematollahi, Rouhollah Bagheri, Fatemeh Fazl, Roohallah Alizadehsani, Reza Lashgari, Ashis Talukder
The superiority of BERT models over other deep models in sentiment analysis is evident and can be concluded from the comparison of the various research studies mentioned in this article.
no code implementations • 26 Oct 2022 • Mahboobeh Jafari, Afshin Shoeibi, Marjane Khodatars, Navid Ghassemi, Parisa Moridian, Niloufar Delfan, Roohallah Alizadehsani, Abbas Khosravi, Sai Ho Ling, Yu-Dong Zhang, Shui-Hua Wang, Juan M. Gorriz, Hamid Alinejad Rokny, U. Rajendra Acharya
Next, the discussion section discusses the results of this review, and future work in CVDs diagnosis from CMR images and DL techniques are outlined.
no code implementations • 26 Oct 2022 • Mahboobeh Jafari, Afshin Shoeibi, Navid Ghassemi, Jonathan Heras, Sai Ho Ling, Amin Beheshti, Yu-Dong Zhang, Shui-Hua Wang, Roohallah Alizadehsani, Juan M. Gorriz, U. Rajendra Acharya, Hamid Alinejad Rokny
The proposed CADS consists of several steps, including dataset, preprocessing, feature extraction, classification, and post-processing.
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.
no code implementations • 20 Jun 2022 • Parisa Moridian, Navid Ghassemi, Mahboobeh Jafari, Salam Salloum-Asfar, Delaram Sadeghi, Marjane Khodatars, Afshin Shoeibi, Abbas Khosravi, Sai Ho Ling, Abdulhamit Subasi, Roohallah Alizadehsani, Juan M. Gorriz, Sara A Abdulla, U. Rajendra Acharya
We review several CADS that have been developed using ML techniques for the automated diagnosis of ASD using MRI modalities.
no code implementations • 23 Mar 2022 • Javad Hassannataj Joloudari, Sanaz Mojrian, Hamid Saadatfar, Issa Nodehi, Fatemeh Fazl, Sahar Khanjani Shirkharkolaie, Roohallah Alizadehsani, H M Dipu Kabir, Ru-San Tan, U Rajendra Acharya
In this paper, according to the latest scientific achievements, a comprehensive literature study (CLS) on artificial intelligence methods based on resource allocation optimization without considering auction-based methods in various computing environments are provided such as cloud computing, Vehicular Fog Computing, wireless, IoT, vehicular networks, 5G networks, vehicular cloud architecture, machine-to-machine communication(M2M), Train-to-Train(T2T) communication network, Peer-to-Peer(P2P) network.
no code implementations • 9 Feb 2022 • Javad Hassannataj Joloudari, Hamid Saadatfar, Mohammad GhasemiGol, Roohallah Alizadehsani, Zahra Alizadeh Sani, Fereshteh Hasanzadeh, Edris Hassannataj, Danial Sharifrazi, Zulkefli Mansor
First, the labeled dataset is applied to the NN and DNN to create the NN and DNN models.
no code implementations • 12 Sep 2021 • Assef Zare, Afshin Shoeibi, Narges Shafaei, Parisa Moridian, Roohallah Alizadehsani, Majid Halaji, Abbas Khosravi
The current survey proposes a triangular type-2 fuzzy regression (TT2FR) model to ameliorate the efficiency of the model by handling the uncertainty in the data.
no code implementations • 12 Sep 2021 • Mohamad Roshanzamir, Roohallah Alizadehsani, Mahdi Roshanzamir, Afshin Shoeibi, Juan M. Gorriz, Abbas Khosrave, Saeid Nahavandi
Their positions and directions were exploited for automatic facial expression recognition using different data mining techniques.
Facial Expression Recognition Facial Expression Recognition (FER) +1
no code implementations • 6 Sep 2021 • Afshin Shoeibi, Navid Ghassemi, Marjane Khodatars, Parisa Moridian, Roohallah Alizadehsani, Assef Zare, Abbas Khosravi, Abdulhamit Subasi, U. Rajendra Acharya, J. Manuel Gorriz
The tunable-Q wavelet transform (TQWT) is employed to decompose the EEG signals into different sub-bands.
no code implementations • 2 Sep 2021 • Afshin Shoeibi, Delaram Sadeghi, Parisa Moridian, Navid Ghassemi, Jonathan Heras, Roohallah Alizadehsani, Ali Khadem, Yinan Kong, Saeid Nahavandi, Yu-Dong Zhang, Juan M. Gorriz
In this step, the DL models were implemented and compared with different activation functions.
no code implementations • 23 Jul 2021 • Javad Hassannataj Joloudari, Faezeh Azizi, Mohammad Ali Nematollahi, Roohallah Alizadehsani, Edris Hassannataj, Amir Mosavi
One of the alternative solutions is the use of machine learning-based patterns for CAD diagnosis.
no code implementations • 5 Jul 2021 • Javad Hassannataj Joloudari, Sanaz Mojrian, Issa Nodehi, Amir Mashmool, Zeynab Kiani Zadegan, Sahar Khanjani Shirkharkolaie, Roohallah Alizadehsani, Tahereh Tamadon, Samiyeh Khosravi, Mitra Akbari Kohnehshari, Edris Hassannatajjeloudari, Danial Sharifrazi, Amir Mosavi, Hui Wen Loh, Ru-San Tan, U Rajendra Acharya
Artificial intelligence-based methods can be utilized to screen for or diagnose MI automatically using ECG signals.
no code implementations • 29 May 2021 • Afshin Shoeibi, Parisa Moridian, Marjane Khodatars, Navid Ghassemi, Mahboobeh Jafari, Roohallah Alizadehsani, Yinan Kong, Juan Manuel Gorriz, Javier Ramírez, Abbas Khosravi, Saeid Nahavandi, U. Rajendra Acharya
In the discussion section, a comparison has been carried out between research on epileptic seizure detection and prediction.
no code implementations • 11 May 2021 • Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, Parisa Moridian, Mitra Rezaei, Roohallah Alizadehsani, Fahime Khozeimeh, Juan Manuel Gorriz, Jónathan Heras, Maryam Panahiazar, Saeid Nahavandi, U. Rajendra Acharya
In this paper, a complete review of automated MS diagnosis methods performed using DL techniques with MRI neuroimaging modalities are discussed.
no code implementations • 28 Apr 2021 • Nooshin Ayoobi, Danial Sharifrazi, Roohallah Alizadehsani, Afshin Shoeibi, Juan M. Gorriz, Hossein Moosaei, Abbas Khosravi, Saeid Nahavandi, Abdoulmohammad Gholamzadeh Chofreh, Feybi Ariani Goni, Jiri Jaromir Klemes, Amir Mosavi
This study is novel as it carries out a comprehensive evaluation of the aforementioned three deep learning methods and their bidirectional extensions to perform prediction on COVID-19 new cases and new death rate time series.
no code implementations • 18 Apr 2021 • Fahime Khozeimeh, Danial Sharifrazi, Navid Hoseini Izadi, Javad Hassannataj Joloudari, Afshin Shoeibi, Roohallah Alizadehsani, Juan M. Gorriz, Sadiq Hussain, Zahra Alizadeh Sani, Hossein Moosaei, Abbas Khosravi, Saeid Nahavandi, Sheikh Mohammed Shariful Islam
To show that clinical data can be used for COVID-19 survival chance prediction, the CNN-AE was compared with multiple pre-trained deep models that were tuned based on CT images.
no code implementations • 24 Feb 2021 • Delaram Sadeghi, Afshin Shoeibi, Navid Ghassemi, Parisa Moridian, Ali Khadem, Roohallah Alizadehsani, Mohammad Teshnehlab, Juan M. Gorriz, Fahime Khozeimeh, Yu-Dong Zhang, Saeid Nahavandi, U Rajendra Acharya
Future works in diagnosing SZ using AI techniques and MRI modalities are recommended in another section.
no code implementations • 13 Feb 2021 • Danial Sharifrazi, Roohallah Alizadehsani, Mohamad Roshanzamir, Javad Hassannataj Joloudari, Afshin Shoeibi, Mahboobeh Jafari, Sadiq Hussain, Zahra Alizadeh Sani, Fereshteh Hasanzadeh, Fahime Khozeimeh, Abbas Khosravi, Saeid Nahavandi, Maryam Panahiazar, Assef Zare, Sheikh Mohammed Shariful Islam, U Rajendra Acharya
In this study, a fusion of convolutional neural network (CNN), support vector machine (SVM), and Sobel filter is proposed to detect COVID-19 using X-ray images.
no code implementations • 12 Feb 2021 • Roohallah Alizadehsani, Danial Sharifrazi, Navid Hoseini Izadi, Javad Hassannataj Joloudari, Afshin Shoeibi, Juan M. Gorriz, Sadiq Hussain, Juan E. Arco, Zahra Alizadeh Sani, Fahime Khozeimeh, Abbas Khosravi, Saeid Nahavandi, Sheikh Mohammed Shariful Islam, U Rajendra Acharya
Our system is capable of learning from a mixture of limited labeled and unlabeled data where supervised learners fail due to a lack of sufficient amount of labeled data.
no code implementations • 22 Dec 2020 • Hamzeh Asgharnezhad, Afshar Shamsi, Roohallah Alizadehsani, Abbas Khosravi, Saeid Nahavandi, Zahra Alizadeh Sani, Dipti Srinivasan
Accordingly, uncertainty quantification methods are capable of flagging risky predictions with high uncertainty estimates.
no code implementations • 23 Aug 2020 • Roohallah Alizadehsani, Mohamad Roshanzamir, Sadiq Hussain, Abbas Khosravi, Afsaneh Koohestani, Mohammad Hossein Zangooei, Moloud Abdar, Adham Beykikhoshk, Afshin Shoeibi, Assef Zare, Maryam Panahiazar, Saeid Nahavandi, Dipti Srinivasan, Amir F. Atiya, U. Rajendra Acharya
We have little knowledge about the optimal treatment methods as there are many sources of uncertainty in medical science.
no code implementations • 16 Jul 2020 • Afshin Shoeibi, Marjane Khodatars, Mahboobeh Jafari, Navid Ghassemi, Delaram Sadeghi, Parisa Moridian, Ali Khadem, Roohallah Alizadehsani, Sadiq Hussain, Assef Zare, Zahra Alizadeh Sani, Fahime Khozeimeh, Saeid Nahavandi, U. Rajendra Acharya, Juan M. Gorriz
Additionally, a review of papers on the forecasting of coronavirus prevalence in different parts of the world with DL is presented.
no code implementations • 2 Jul 2020 • Marjane Khodatars, Afshin Shoeibi, Delaram Sadeghi, Navid Ghassemi, Mahboobeh Jafari, Parisa Moridian, Ali Khadem, Roohallah Alizadehsani, Assef Zare, Yinan Kong, Abbas Khosravi, Saeid Nahavandi, Sadiq Hussain, U. Rajendra Acharya, Michael Berk
Due to the intricate structure and function of the brain, proposing optimum procedures for ASD diagnosis with neuroimaging data without exploiting powerful AI techniques like DL may be challenging.
no code implementations • 2 Jul 2020 • Afshin Shoeibi, Marjane Khodatars, Navid Ghassemi, Mahboobeh Jafari, Parisa Moridian, Roohallah Alizadehsani, Maryam Panahiazar, Fahime Khozeimeh, Assef Zare, Hossein Hosseini-Nejad, Abbas Khosravi, Amir F. Atiya, Diba Aminshahidi, Sadiq Hussain, Modjtaba Rouhani, Saeid Nahavandi, Udyavara Rajendra Acharya
The important challenges in accurate detection of automated epileptic seizures using DL with EEG and MRI modalities are discussed.
no code implementations • 29 Jun 2020 • Hadi Mahami, Navid Ghassemi, Mohammad Tayarani Darbandy, Afshin Shoeibi, Sadiq Hussain, Farnad Nasirzadeh, Roohallah Alizadehsani, Darius Nahavandi, Abbas Khosravi, Saeid Nahavandi
Recent advancements in Artificial intelligence, especially deep learning, has changed many fields irreversibly by introducing state of the art methods for automation.