Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Mohammadjavad Sayadi"'
Autor:
Mostafa Langarizadeh, Fateme Moghbeli, Shamim Ahmadi, Mohammad Hossein Langarizadeh, Mohammadjavad Sayadi, Fatemeh Sarpourian, Seyed Ali Fatemi Aghda
Publikováno v:
BMC Health Services Research, Vol 23, Iss 1, Pp 1-8 (2023)
Abstract Background Liver transplantation, the last treatment for advanced liver failure, necessitates patient education due to its wide range of complications and subsequent disabilities. The present study was development-applied research and aimed
Externí odkaz:
https://doaj.org/article/deaf2d1830114d5cbf37470dfaf48038
Publikováno v:
Advanced Biomedical Research, Vol 13, Iss 1, Pp 55-55 (2024)
Background: Self-immolation is one of the violent methods of suicide in developing countries. Predicting the survival of self-immolation patients helps develop therapeutic strategies. Today, machine learning is widely used in diagnosing diseases and
Externí odkaz:
https://doaj.org/article/d1d4ebb5598b4b98bcec903f0d6ce295
Autor:
Mohammadjavad Sayadi, Vijayakumar Varadarajan, Farahnaz Sadoughi, Sara Chopannejad, Mostafa Langarizadeh
Publikováno v:
Life, Vol 12, Iss 11, p 1933 (2022)
Background and Objective: Coronary artery disease (CAD) is one of the most prevalent causes of death worldwide. The early diagnosis and timely medical care of cardiovascular patients can greatly prevent death and reduce the cost of treatments associa
Externí odkaz:
https://doaj.org/article/6b4f58af8e134386b3203fd721080626
Autor:
Mohammadjavad Sayadi, Vijayakumar Varadarajan, Mostafa Langarizadeh, Gholamreza Bayazian, Farhad Torabinezhad
Publikováno v:
Electronics. 11:4235
There is a substantial unmet need to diagnose speech-related disorders effectively. Machine learning (ML), as an area of artificial intelligence (AI), enables researchers, physicians, and patients to solve these issues. The purpose of this study was
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba72903d4d7b788c6be03cfc4ef1df51
https://doi.org/10.3390/electronics11244235
https://doi.org/10.3390/electronics11244235