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Roohallah Alizadehsani

Roohallah Alizadehsani

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Rising Stars
2025

D-Index & Metrics

Rising Stars

D-Index
45
Citations
6899
World Ranking
456
National Ranking
30

Computer Science

D-Index
49
Citations
8204
World Ranking
5953
National Ranking
182

Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Roohallah Alizadehsani is a researcher affiliated with Deakin University in Australia. Their work spans various aspects of medicine and computer science, with a substantial focus on artificial intelligence and its application in healthcare.

Their main fields of study include:

  • Medicine
  • Computer Science

Within these fields, their subfields of expertise comprise:

  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Cardiology and Cardiovascular Medicine
  • Cognitive Neuroscience

Roohallah Alizadehsani's primary research topics cover:

  • COVID-19 diagnosis using AI
  • Artificial Intelligence in Healthcare
  • Machine Learning in Healthcare
  • EEG and Brain-Computer Interfaces
  • Anomaly Detection Techniques and Applications
  • AI in cancer detection
  • Brain Tumor Detection and Classification

Several recent papers showcase the scope and focus of their research:

  • Epileptic Seizures Detection Using Deep Learning Techniques: A Review (2021), International Journal of Environmental Research and Public Health
  • Application of artificial intelligence in wearable devices: Opportunities and challenges (2021), Computer Methods and Programs in Biomedicine
  • Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review (2020), arXiv (Cornell University)
  • A review of Explainable Artificial Intelligence in healthcare (2024), Computers & Electrical Engineering
  • Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review (2021), Computers in Biology and Medicine

Frequent collaborators include:

  • U. Rajendra Acharya
  • Abbas Khosravi
  • Saeid Nahavandi
  • Afshin Shoeibi
  • Sadiq Hussain

The venues where Roohallah Alizadehsani publishes most frequently are:

  • arXiv (Cornell University)
  • IEEE Access
  • Computers in Biology and Medicine
  • Scientific Reports
  • Research Square (Research Square)

Best Publications

  • Computer aided decision making for heart disease detection using hybrid neural network-Genetic algorithm

    Zeinab Arabasadi;Roohallah Alizadehsani;Mohamad Roshanzamir;Hossein Moosaei

  • Epileptic Seizures Detection Using Deep Learning Techniques: A Review.

    Afshin Shoeibi;Marjane Khodatars;Navid Ghassemi;Navid Ghassemi;Mahboobeh Jafari

  • A data mining approach for diagnosis of coronary artery disease

    Roohallah Alizadehsani;Jafar Habibi;Mohammad Javad Hosseini;Hoda Mashayekhi

  • Application of artificial intelligence in wearable devices: Opportunities and challenges.

    Darius Nahavandi;Roohallah Alizadehsani;Abbas Khosravi;U Rajendra Acharya

  • Machine learning-based coronary artery disease diagnosis: A comprehensive review.

    Roohallah Alizadehsani;Moloud Abdar;Mohamad Roshanzamir;Abbas Khosravi

  • Deep learning for neuroimaging-based diagnosis and rehabilitation of Autism Spectrum Disorder: A review.

    Marjane Khodatars;Afshin Shoeibi;Afshin Shoeibi;Delaram Sadeghi;Navid Ghaasemi

  • An expert system for selecting wart treatment method

    Fahime Khozeimeh;Roohallah Alizadehsani;Mohamad Roshanzamir;Abbas Khosravi

  • Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review

    Afshin Shoeibi;Marjane Khodatars;Roohallah Alizadehsani;Navid Ghassemi

  • Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review.

    Afshin Shoeibi;Marjane Khodatars;Mahboobeh Jafari;Parisa Moridian

  • Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models

    Afshin Shoeibi;Delaram Sadeghi;Parisa Moridian;Navid Ghassemi

  • The internet of medical things and artificial intelligence: trends, challenges, and opportunities

    Unknown

  • Coronary artery disease detection using computational intelligence methods

    Roohallah Alizadehsani;Mohammad Hossein Zangooei;Mohammad Javad Hosseini;Jafar Habibi

  • An Overview on Artificial Intelligence Techniques for Diagnosis of Schizophrenia Based on Magnetic Resonance Imaging Modalities: Methods, Challenges, and Future Works.

    Delaram Sadeghi;Afshin Shoeibi;Navid Ghassemi;Parisa Moridian

  • Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images.

    Danial Sharifrazi;Roohallah Alizadehsani;Mohamad Roshanzamir;Javad Hassannataj Joloudari

  • A comprehensive comparison of handcrafted features and convolutional autoencoders for epileptic seizures detection in EEG signals

    Afshin Shoeibi;Navid Ghassemi;Roohallah Alizadehsani;Modjtaba Rouhani

  • Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods.

    Nooshin Ayoobi;Danial Sharifrazi;Roohallah Alizadehsani;Afshin Shoeibi;Afshin Shoeibi

  • Detection of Epileptic Seizures on EEG Signals Using ANFIS Classifier, Autoencoders and Fuzzy Entropies.

    Afshin Shoeibi;Navid Ghassemi;Marjane Khodatars;Parisa Moridian

  • Non-invasive detection of coronary artery disease in high-risk patients based on the stenosis prediction of separate coronary arteries

    Roohallah Alizadehsani;Mohammad Javad Hosseini;Abbas Khosravi;Fahime Khozeimeh

  • Association between work-related features and coronary artery disease: A heterogeneous hybrid feature selection integrated with balancing approach

    Elham Nasarian;Moloud Abdar;Mohammad Amin Fahami;Roohallah Alizadehsani

  • Robust Adaptive Control Scheme for Teleoperation Systems With Delay and Uncertainties

    Parham M. Kebria;Abbas Khosravi;Saeid Nahavandi;Peng Shi

  • Combining a convolutional neural network with autoencoders to predict the survival chance of COVID-19 patients.

    Fahime Khozeimeh;Danial Sharifrazi;Navid Hoseini Izadi;Javad Hassannataj Joloudari

  • Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991–2020)

    Roohallah Alizadehsani;Mohamad Roshanzamir;Sadiq Hussain;Abbas Khosravi

  • Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review

    Marjane Khodatars;Afshin Shoeibi;Navid Ghassemi;Mahboobeh Jafari

Frequent Co-Authors

Saeid Nahavandi
Saeid Nahavandi Swinburne University of Technology
Abbas Khosravi
Abbas Khosravi Deakin University
U. Rajendra Acharya
U. Rajendra Acharya University of Southern Queensland
Juan Manuel Górriz
Juan Manuel Górriz University of Granada
Moloud Abdar
Moloud Abdar Deakin University
Amir Mosavi
Amir Mosavi Óbuda University
Sheikh Mohammed Shariful Islam
Sheikh Mohammed Shariful Islam Texas Tech University
Amir F. Atiya
Amir F. Atiya Cairo University
Colette M. McKay
Colette M. McKay Bionics Institute
Dipti Srinivasan
Dipti Srinivasan National University of Singapore

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