Monkeypox detection using deep neural networks

Autor: Amir Sorayaie Azar, Amin Naemi, Samin Babaei Rikan, Jamshid Bagherzadeh Mohasefi, Habibollah Pirnejad, Uffe Kock Wiil

Publikováno v: BMC Infectious Diseases, Vol 23, Iss 1, Pp 1-13 (2023)

Abstract Background In May 2022, the World Health Organization (WHO) European Region announced an atypical Monkeypox epidemic in response to reports of numerous cases in some member countries unrelated to those where the illness is endemic. This issu

Externí odkaz: https://doaj.org/article/8edc92d86c934d80911a10ee573d9de6

Identification of clinical factors related to prediction of alcohol use disorder from electronic health records using feature selection methods

Autor: Ali Ebrahimi, Uffe Kock Wiil, Amin Naemi, Marjan Mansourvar, Kjeld Andersen, Anette Søgaard Nielsen

Publikováno v: BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-25 (2022)

Abstract Background High dimensionality in electronic health records (EHR) causes a significant computational problem for any systematic search for predictive, diagnostic, or prognostic patterns. Feature selection (FS) methods have been indicated to

Externí odkaz: https://doaj.org/article/7c57513cdc254c9a96531e2a3eba456c

Predicting the Risk of Alcohol Use Disorder Using Machine Learning: A Systematic Literature Review

Autor: Ali Ebrahimi, Uffe Kock Wiil, Thomas Schmidt, Amin Naemi, Anette Sogaard Nielsen, Ghulam Mujtaba Shaikh, Marjan Mansourvar

Publikováno v: IEEE Access, Vol 9, Pp 151697-151712 (2021)

The number of deaths caused by alcohol-related diseases may be reduced by predicting alcohol use disorder (AUD). Many researchers have worked on AUD prediction using machine learning (ML) techniques. However, to the best of our knowledge, there is a

Externí odkaz: https://doaj.org/article/3637a16e2a664c78b4e223243639a61e

Predicting the Risk of Alcohol Use Disorder Using Machine Learning: A Systematic Literature Review

Autor: Marjan Mansourvar, Uffe Kock Wiil, Anette Søgaard Nielsen, Ghulam Mujtaba Shaikh, Ali Ebrahimi, Thomas Schmidt, Amin Naemi

Publikováno v: IEEE Access, Vol 9, Pp 151697-151712 (2021)
Ebrahimi, A, Wiil, U K, Schmidt, T, Naemi, A, Nielsen, A S, Shaikh, G M & Mansourvar, M 2021, ' Predicting the Risk of Alcohol Use Disorder Using Machine Learning : A Systematic Literature Review ', IEEE Access, vol. 9, pp. 151697-151712 . https://doi.org/10.1109/ACCESS.2021.3126777

The number of deaths caused by alcohol-related diseases may be reduced by predicting alcohol use disorder (AUD). Many researchers have worked on AUD prediction using machine learning (ML) techniques. However, to the best of our knowledge, there is a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::daece4805b9a91e398404d44ab54df34
https://ieeexplore.ieee.org/document/9606822/

Modeling and Evaluating the Impact of Social Restrictions on the Spread of COVID-19 Using Machine Learning

Autor: Mostafa Naemi, Amin Naemi, Romina Zarrabi Ekbatani, Ali Ebrahimi, Thomas Schmidt, Uffe Kock Wiil

Publikováno v: Naemi, M, Naemi, A, Ekbatani, R Z, Ebrahimi, A, Schmidt, T & Wiil, U K 2022, Modeling and Evaluating the Impact of Social Restrictions on the Spread of COVID-19 Using Machine Learning . in R J Howlett, L C Jain, J R Littlewood & M M Balas (eds), Smart and Sustainable Technology for Resilient Cities and Communities . Springer, Advances in Sustainability Science and Technology, pp. 107-118 . https://doi.org/10.1007/978-981-16-9101-0_8
Advances in Sustainability Science and Technology ISBN: 9789811691003

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6189e09db1b2f91185cc3000edde82e
https://portal.findresearcher.sdu.dk/da/publications/0ea88f29-e24c-4c74-be0e-4364174e4fd8