A Review on Adverse Drug Reaction Detection Techniques

Keywords: Adverse drug reactions, Detection, Machine learning, Deep learning, Sentiment analysis, Trigger terms


The detection of adverse drug reactions (ADRs) is an important piece of information for determining a patient’s view of a single drug. This study attempts to consider and discuss this feature of drug reviews in medical opinion-mining systems. This paper discusses the literature that summarizes the background of this work. To achieve this aim, the first discusses a survey on detecting ADRs and side effects, followed by an examination of biomedical text mining that focuses on identifying the specific relationships involving ADRs. Finally, we will provide a general overview of sentiment analysis, particularly from a medical perspective. This study presents a survey on ADRs extracted from drug review sentences on social media, utilizing and comparing different techniques.


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Author Biographies

Ahmed A. Nafea, Department of Artificial Intelligence, College of Computer Science and IT, University of Anbar, Ramadi, Iraq

Ahmed Adil Nafea is a Lecturer at the Department of Artificial Intelligence, College of Computer Science and IT, University of Anbar, Ramadi, Iraq. He got the B.Sc. degree in Information System, the M.Sc. degree in Artificial Intelligence. His research interests are in artificial intelligence, machine learning, deep learning, and natural language processing. Mr. Ahmed is an Honorary member of the Golden Key International Honour Society: in Atlanta, GA, US.

Manar AL-Mahdawi, Department of Medical Physics, College of Science, Al-Nahrain University, Jadriya, Baghdad, 10072, Iraq

Manar AL-Mahdawi is a Lecturer at the Department of Medical Physics, College of Science, Al-Nahrain University, Jadriya, Baghdad, Iraq. His research interests are in artificial intelligence, machine learning, deep learning.

Mohammed M. AL-Ani , Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

Mohammed M. AL-Ani is a Researcher at the Center for Artificial Intelligence Technology (CAIT), FTSM, UKM and he is working at the water resources of Anbar, Ramadi, Iraq. He got the B.Sc. degree in Information System, the M.Sc. degree in Artificial Intelligence. His research interests are in artificial intelligence, machine learning, deep learning, and natural language processing. Mr. Mohammed is an Honorary member of the Golden Key International Honour Society: in Atlanta, GA, US.

Nazlia Omar , Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

Nazlia Omar is an Associate Professor at the Faculty of Information Science and Technology at Universiti Kebangsaan Malaysia (UKM). She received the B.Sc. degree in Computer Science, the M.Sc. degree in Information Systems and the Ph.D. degree in Natural Language Processing. Her research interests are in natural language processing, with particular focus on Malay, English and Arabic language processing issues. Dr. Nazlia is a member of the Center for Artificial Intelligence Technology (CAIT), FTSM.


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How to Cite
Nafea, A. A., AL-Mahdawi, M., AL-Ani , M. M. and Omar , N. (2024) “A Review on Adverse Drug Reaction Detection Techniques”, ARO-THE SCIENTIFIC JOURNAL OF KOYA UNIVERSITY, 12(1), pp. 143-153. doi: 10.14500/aro.11388.
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