TR-Dizin İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/9

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  • Article
    Artificial Neural Networks in Drug Addiction Diagnosis
    (2025) Karaman, Engin
    This study aims to find a simple mechanism to help researchers and families identify addicts. In this paper, the Artificial Neural Network (ANN) method has been examined to determine whether a person is an addict. In this study, the dataset obtained from students from different countries and published as open source by Atif Masih was used. This dataset contains 50343 samples with 11 features. The study involved testing and comparing multiple neural network architectures based on their average classification accuracy. When the correlation matrix is examined, it is seen that the relationships between the variables are almost negligible. This can be attributed to the fact that the variables are categorical. Each architecture was trained using 10 different seed numbers, and the mean accuracy was calculated accordingly. The experiment results have obtained 75.53% classification accuracy for correct diagnosis in our system. Our model could significantly expedite the diagnosis and treatment of addiction, providing a valuable tool for families, physicians, and investigators. The paper proposes a Decision Support System (DSS) for diagnosing addiction, leveraging one of the most widely-used machine learning techniques: Artificial Neural Networks (ANN).
  • Article
    Life and Stigma Experiences of Individuals with Substance Use Disorder: A Qualitative Study
    (Turkish Green Crescent Soc, 2025) Dikec, Gul; Umut, Gokhan; Albal, Esra
    This study aimed to determine the life and stigma experiences of individuals with substance use disorder who received inpatient treatment in an adult detoxification center. Data for this qualitative phenomenological study were collected in Istanbul between April and December 2023. The data were analyzed using Colazzi steps. A total of 26 individuals with substance use disorder were interviewed. The content analysis identified three main themes. The initial topic discussed was the effect of substance use on individuals’ lives. The sec- ond theme discussed was stigmatization. The final theme addressed coping with stigmatization. The study revealed that participants experienced negative emotions, including regret, guilt, and shame, due to stigma- tization, exclusion, and discrimination. Substance use treatment should not only focus on pharmacotherapy but also the psychological and social needs of the individual. Furthermore, to address negative attitudes in society, mental health professionals could inform families and disseminate anti-stigma programs.