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.
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 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 • 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 • 31 May 2022 • Afshin Shoeibi, Navid Ghassemi, Marjane Khodatars, Parisa Moridian, Abbas Khosravi, Assef Zare, Juan M. Gorriz, Amir Hossein Chale-Chale, Ali Khadem, U. Rajendra Acharya
So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) and attention deficit hyperactivity disorder (ADHD), among which functional magnetic resonance imaging (fMRI) modalities are known as a popular method among physicians.
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 • 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 • 24 Apr 2021 • Navid Ghassemi, Afshin Shoeibi, Marjane Khodatars, Jonathan Heras, Alireza Rahimi, Assef Zare, Ram Bilas Pachori, J. Manuel Gorriz
Also, in order to evaluate the method, a dataset containing 3163 images from 189 patients has been collected and labeled by physicians.
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 • 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.