Výsledky vyhledávání - "Sani, Zahra Alizadeh"

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FCM-DNN: diagnosing coronary artery disease by deep accuracy Fuzzy C-Means clustering model

Autor: Joloudari, Javad Hassannataj, Saadatfar, Hamid, GhasemiGol, Mohammad, Alizadehsani, Roohallah, Sani, Zahra Alizadeh, Hasanzadeh, Fereshteh, Hassannataj, Edris, Sharifrazi, Danial, Mansor, Zulkefli

Cardiovascular disease is one of the most challenging diseases in middle-aged and older people, which causes high mortality. Coronary artery disease (CAD) is known as a common cardiovascular disease. A standard clinical tool for diagnosing CAD is ang

Externí odkaz: http://arxiv.org/abs/2202.04645

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Akademický článek

Automated detection and forecasting of COVID-19 using deep learning techniques: A review

Autor: Shoeibi, Afshin, Khodatars, Marjane, Jafari, Mahboobeh, Ghassemi, Navid, Sadeghi, Delaram, Moridian, Parisa, Khadem, Ali, Alizadehsani, Roohallah, Hussain, Sadiq, Zare, Assef, Sani, Zahra Alizadeh, Khozeimeh, Fahime, Nahavandi, Saeid, Acharya, U. Rajendra, Gorriz, Juan M.

Publikováno v: In Neurocomputing 7 April 2024 577

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Combining a Convolutional Neural Network with Autoencoders to Predict the Survival Chance of COVID-19 Patients

Autor: Khozeimeh, Fahime, Sharifrazi, Danial, Izadi, Navid Hoseini, Joloudari, Javad Hassannataj, Shoeibi, Afshin, Alizadehsani, Roohallah, Gorriz, Juan M., Hussain, Sadiq, Sani, Zahra Alizadeh, Moosaei, Hossein, Khosravi, Abbas, Nahavandi, Saeid, Islam, Sheikh Mohammed Shariful

Publikováno v: Scientific Reports, 11(1), 1-18 (2021)

COVID-19 has caused many deaths worldwide. The automation of the diagnosis of this virus is highly desired. Convolutional neural networks (CNNs) have shown outstanding classification performance on image datasets. To date, it appears that COVID compu

Externí odkaz: http://arxiv.org/abs/2104.08954

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

Autor: Sharifrazi, Danial, Alizadehsani, Roohallah, Roshanzamir, Mohamad, Joloudari, Javad Hassannataj, Shoeibi, Afshin, Jafari, Mahboobeh, Hussain, Sadiq, Sani, Zahra Alizadeh, Hasanzadeh, Fereshteh, Khozeimeh, Fahime, Khosravi, Abbas, Nahavandi, Saeid, Panahiazar, Maryam, Zare, Assef, Islam, Sheikh Mohammed Shariful, Acharya, U Rajendra

The coronavirus (COVID-19) is currently the most common contagious disease which is prevalent all over the world. The main challenge of this disease is the primary diagnosis to prevent secondary infections and its spread from one person to another. T

Externí odkaz: http://arxiv.org/abs/2102.06883

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Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data

Autor: Alizadehsani, Roohallah, Sharifrazi, Danial, Izadi, Navid Hoseini, Joloudari, Javad Hassannataj, Shoeibi, Afshin, Gorriz, Juan M., Hussain, Sadiq, Arco, Juan E., Sani, Zahra Alizadeh, Khozeimeh, Fahime, Khosravi, Abbas, Nahavandi, Saeid, Islam, Sheikh Mohammed Shariful, Acharya, U Rajendra

Publikováno v: ACM Transactions on Multimedia Computing, Communications, and ApplicationsVolume 17Issue 3sOctober 2021

The new coronavirus has caused more than one million deaths and continues to spread rapidly. This virus targets the lungs, causing respiratory distress which can be mild or severe. The X-ray or computed tomography (CT) images of lungs can reveal whet

Externí odkaz: http://arxiv.org/abs/2102.06388

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Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection

Autor: Asgharnezhad, Hamzeh, Shamsi, Afshar, Alizadehsani, Roohallah, Khosravi, Abbas, Nahavandi, Saeid, Sani, Zahra Alizadeh, Srinivasan, Dipti

Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of

Externí odkaz: http://arxiv.org/abs/2012.11840

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