Zobrazeno 1 - 10
of 1 141
pro vyhledávání: '"Pourhoseingholi, A"'
Autor:
Ghaffarzadeh-Esfahani, Mohammadreza, Ghaffarzadeh-Esfahani, Mahdi, Salahi-Niri, Arian, Toreyhi, Hossein, Atf, Zahra, Mohsenzadeh-Kermani, Amirali, Sarikhani, Mahshad, Tajabadi, Zohreh, Shojaeian, Fatemeh, Bagheri, Mohammad Hassan, Feyzi, Aydin, Tarighatpayma, Mohammadamin, Gazmeh, Narges, Heydari, Fateme, Afshar, Hossein, Allahgholipour, Amirreza, Alimardani, Farid, Salehi, Ameneh, Asadimanesh, Naghmeh, Khalafi, Mohammad Amin, Shabanipour, Hadis, Moradi, Ali, Zadeh, Sajjad Hossein, Yazdani, Omid, Esbati, Romina, Maleki, Moozhan, Nasr, Danial Samiei, Soheili, Amirali, Majlesi, Hossein, Shahsavan, Saba, Soheilipour, Alireza, Goudarzi, Nooshin, Taherifard, Erfan, Hatamabadi, Hamidreza, Samaan, Jamil S, Savage, Thomas, Sakhuja, Ankit, Soroush, Ali, Nadkarni, Girish, Darazam, Ilad Alavi, Pourhoseingholi, Mohamad Amin, Safavi-Naini, Seyed Amir Ahmad
Background: This study aimed to evaluate and compare the performance of classical machine learning models (CMLs) and large language models (LLMs) in predicting mortality associated with COVID-19 by utilizing a high-dimensional tabular dataset. Materi
Externí odkaz:
http://arxiv.org/abs/2409.02136
Autor:
Masoomeh Raoufi, Mahsa Hojabri, Danial Samiei Nasr, Hanieh Najafiarab, Aryan Salahi-Niri, Nastaran Ebrahimi, Shideh Ariana, Hamidreza Khodabandeh, Sara Salarian, Mehdi Azizmohammad Looha, Mohamad Amin Pourhoseingholi, Seyed Amir Ahmad Safavi-Naini
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract This study aimed to assess the severity and outcomes of COVID-19 in pregnant women, focusing on laboratory and radiological discrepancies between pregnant women and matched nonpregnant women. In this retrospective cross-sectional analysis, w
Externí odkaz:
https://doaj.org/article/56c76f24396e4b94a54a71e13baa5af8
Autor:
Farideh Mohtasham, MohamadAmin Pourhoseingholi, Seyed Saeed Hashemi Nazari, Kaveh Kavousi, Mohammad Reza Zali
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract In the context of early disease detection, machine learning (ML) has emerged as a vital tool. Feature selection (FS) algorithms play a crucial role in ensuring the accuracy of predictive models by identifying the most influential variables.
Externí odkaz:
https://doaj.org/article/95816bbc96144c08bccbeff10a68d6ad
Autor:
Barati, Hadis1 (AUTHOR) hbarati7@gmail.com, Pourhoseingholi, Mohamad Amin2 (AUTHOR) aminphg@gmail.com, Roshandel, Gholamreza3 (AUTHOR) Roshandel_md@yahoo.com, Nazari, Seyed Saeed Hashemi1 (AUTHOR) saeedh_1999@yahoo.com
Publikováno v:
BMC Cancer. 12/18/2024, Vol. 24 Issue 1, p1-9. 9p.
Autor:
Mohtasham, Farideh1 f-mohtasham@sbmu.ac.ir, Pourhoseingholi, MohamadAmin2, Hashemi Nazari, Seyed Saeed3, Kavousi, Kaveh4 kkavousi@ut.ac.ir, Zali, Mohammad Reza1
Publikováno v:
Scientific Reports. 8/15/2024, Vol. 14 Issue 1, p1-20. 20p.
Autor:
Mohamad Amin Pourhoseingholi, Mehdi Azizmohammad Looha, Saba Ilkhani, Hamidreza Hatamabadi, Amir Sadeghi, Seyed Amir Ahmad Safavi-Naini, Kamran Heidari, Nazanin Taraghikhah, Mohammad Mahdi Fallah, Reyhaneh Kalantar, Nariman Naderi, Romina Esbati, Nastaran Ebrahimi, Ali Solhpour, Tannaz Jamialahmadi, Amirhossein Sahebkar
Publikováno v:
Journal of Clinical Virology Plus, Vol 4, Iss 2, Pp 100180- (2024)
Background: This study aimed to evaluate the impact of remdesivir, alone or in combination with corticosteroids, on the time to death in COVID-19 patients. Methods: This retrospective cohort study was conducted between March 20, 2020, and March 18, 2
Externí odkaz:
https://doaj.org/article/0f1ed24ba8c443b5b27875cf16a85a1c
Autor:
Pourhoseingholi, Mohamad Amin, Looha, Mehdi Azizmohammad, Ilkhani, Saba, Hatamabadi, Hamidreza, Sadeghi, Amir, Safavi-Naini, Seyed Amir Ahmad, Heidari, Kamran, Taraghikhah, Nazanin, Fallah, Mohammad Mahdi, Kalantar, Reyhaneh, Naderi, Nariman, Esbati, Romina, Ebrahimi, Nastaran, Solhpour, Ali, Jamialahmadi, Tannaz, Sahebkar, Amirhossein
Publikováno v:
In Journal of Clinical Virology Plus June 2024 4(2)
Autor:
Forootan, Mojgan, Rajabnia, Mohsen, Ghorbanpoor Rassekh, Ahmad, Abdi, Saeed, Fathi, Mobin, Pourhoseingholi, Mohamad Amin, Ketabi Moghadam, Pardis
Publikováno v:
In Arab Journal of Gastroenterology May 2024 25(2):97-101
Autor:
Heidari, Mohammad Eghbal, Irvani, Seyed Sina Naghibi, Pourhoseingholi, Mohamad Amin, Takhtegahi, Mona Maleki, Beyranvand, Rezvane, Mardanparvar, Hossein, Hesami, Hamed, Ghavampour, Neda, Hatami, Hossein
Publikováno v:
In Journal of Affective Disorders 1 February 2024 346:9-20
Autor:
Raheleh Talebi, Carlos A. Celis-Morales, Abolfazl Akbari, Atefeh Talebi, Nasrin Borumandnia, Mohamad Amin Pourhoseingholi
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
BackgroundThe increasing prevalence of colorectal cancer (CRC) in Iran over the past three decades has made it a key public health burden. This study aimed to predict metastasis in CRC patients using machine learning (ML) approaches in terms of demog
Externí odkaz:
https://doaj.org/article/a1b561d7718b4791b6f11128a1d86b8b