Predicting patients' sentiments about medications using artificial intelligence techniques.

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

Publikováno v: Scientific Reports; 12/30/2024, Vol. 14 Issue 1, p1-23, 23p

Quantifying the impact of addressing data challenges in prediction of length of stay.

Autor: Naemi, Amin¹ (AUTHOR) amin@mmmi.sdu.dk, Schmidt, Thomas¹ (AUTHOR), Mansourvar, Marjan² (AUTHOR), Ebrahimi, Ali¹ (AUTHOR), Wiil, Uffe Kock¹ (AUTHOR)

Publikováno v: BMC Medical Informatics & Decision Making. 11/8/2021, Vol. 21 Issue 1, p1-13. 13p.

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Predictive Models for Identifying Clinical Deterioration

Autor: Naemi, Amin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::87f04c071d1f502b7140647fc3079500

Deep Neural Network to Identify Patients with Alcohol Use Disorder

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

Publikováno v: Ebrahimi, A, Wiil, U K, Mansourvar, M, Naemi, A, Andersen, K & Nielsen, A S 2021, Deep Neural Network to Identify Patients with Alcohol Use Disorder . in J Mantas, L Stoicu-Tivadar, C Chronaki, A Hasman, P Weber, P Gallos, M Crişan-Vida, E Zoulias & O S Chirila (eds), Public Health and Informatics . vol. 281, Studies in Health Technology and Informatics, vol. 281, pp. 238-242, MIE 2021: 31st Medical Informatics Europe Conference Online, 29/05/2021 . https://doi.org/10.3233/SHTI210156

This paper presents an application of deep neural networks (DNN) to identify patients with Alcohol Use Disorder based on historical electronic health records. Our methodology consists of four stages including data collection, preprocessing, predictiv

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3062::87787c14d265d929810d2d303bceb375
https://findresearcher.sdu.dk:8443/ws/files/182805498/SHTI_281_SHTI210156.pdf