Large Language Models versus Classical Machine Learning: Performance in COVID-19 Mortality Prediction Using High-Dimensional Tabular Data

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

Clinical predictors of abnormal chest CT scan findings following blunt chest trauma: A cross-sectional study

Autor: Safari, Saeed, Farbod, Melina, Hatamabadi, Hamidreza, Yousefifard, Mahmoud, Mokhtari, Navid

Publikováno v: In Chinese Journal of Traumatology February 2020 23(1):51-55

Epidemiology of COVID-19 in Tehran, Iran: A Cohort Study of Clinical Profile, Risk Factors, and Outcomes.

Autor: Hatamabadi, Hamidreza¹ (AUTHOR), Sabaghian, Tahereh² (AUTHOR), Sadeghi, Amir³ (AUTHOR), Heidari, Kamran⁴ (AUTHOR), Safavi-Naini, Seyed Amir Ahmad⁵ (AUTHOR), Looha, Mehdi Azizmohammad⁶ (AUTHOR), Taraghikhah, Nazanin³ (AUTHOR), Khalili, Shayesteh⁷ (AUTHOR), Karrabi, Keivan⁸ (AUTHOR), Saffarian, Afsaneh⁹ (AUTHOR), Shahsavan, Saba⁵ (AUTHOR), Majlesi, Hossein⁵ (AUTHOR), Allahgholipour Komleh, Amirreza¹⁰ (AUTHOR), Hatari, Saba⁵ (AUTHOR), Zameni, Nadia⁵ (AUTHOR), Ilkhani, Saba⁵ (AUTHOR), Hajimirzaei, Shideh Moftakhari⁵ (AUTHOR), Ghaffari, Aydin⁵ (AUTHOR), Fallah, Mohammad Mahdi⁵ (AUTHOR), Kalantar, Reyhaneh⁵ (AUTHOR)

Publikováno v: BioMed Research International. 5/10/2022, p1-17. 17p.

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