Mohammad Shahadat Hossain, Mohammad Shahadat
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Textual and numerical data fusion for depression detection: a machine learning framework Aziz, Mohammad Tarek; Mahmud, Tanjim; Abdul Aziz, Md Faisal Bin; Siddick, Md Abu Bakar; Sharif, Md. Maskat; Hossain, Mohammad Shahadat; Andersson, Karl
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp1231-1244

Abstract

Depression, a widespread mood disorder, significantly affects global mental health. To mitigate the risk of recurrence, early detection is crucial. This study explores socioeconomic factors contributing to depression and proposes a novel machine learning (ML)-based framework for its detection. We develop a tailored questionnaire to collect textual and numerical data, followed by rigorous feature selection using methods like backward removal and Pearson’s chi-squared test. A variety of ML algorithms, including random forest (RF), support vector machine (SVM), and logistic regression (LR), are employed to create a predictive classifier. The RF model achieves the highest accuracy of 96.85%, highlighting its effectiveness in identifying depression risk factors. This research advances depression detection by integrating socioeconomic analysis with ML, offering a robust tool for enhancing predictive accuracy and enabling proactive mental health interventions.
What is Scientific Reality? Hossain, Mohammad Shahadat
Journal of Critical Realism in Socio-Economics (JOCRISE) Vol. 4 No. 1 (2025): Supercardinal Accountability of Allah, Heaven, and Earth
Publisher : University of Darussalam Gontor Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/jocrise.v4i1.96

Abstract

Scientific progress in AI, Big Data, and FINTECH has revolutionized human life but also intensified inequality, surveillance, and ecological crises. This paper argues that such contradictions arise from modern science’s separation of morality from materiality. It advances the Law of Unity of Knowledge, integrating ethical consciousness (“being”) with empirical reality (“becoming”) through circular causation. The framework, rooted in insights from Einstein, Hawking, Whitehead, and Imam Ghazali, culminates in a Wellbeing Function that links sustainability to moral-material complementarity. Applications include ethical AI in healthcare and Qur’ānic principles of trusteeship in agriculture, redefining scientific reality as holistic, ethical, and transformative