Search
14 articles for “Depression Detection”
-
Depression Detection using Machine Learning: A Comprehensive Review
Abstract: Depression is a leading mental health disorder worldwide, often underdiagnosed due to subjective assessment methods. The increasing availability of digital behavioral data and the advancement in machine learning (ML) have opened new avenues for automated depression detection. This review presents a comprehensive overview of recent developments in ML- based approaches for detecting depression. It explores data sources, feature extraction techniques, learning algorithms, evaluation methods, and highlights current challenges and future …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 Read article
-
Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
-
Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
-
Face Emotion Recognition to Detect Depression
Abstract: In the current competitive world, one of the most familiar and grave mental illness we encounter in humans is Depression also called as major depression or major depressive disorder. It makes you feel depressed and disinterested all the time, which has a bad impact on your thoughts and behaviour. Thus affecting not only the victim but also people associated with them, such as family, friends and society. If not treated …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 1–14 Read article
-
A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
-
The potential Role of Antidepressant Medications in DNA Oxidation of Depression Disorder Cases
Abstract: Oxidative stress and DNA oxidation is a main target of different medications side effect, the current work aims to evaluate the potential role of anti-depressed medications in DNA oxidation in depression disorder cases, reactive oxygen species (ROS), total antioxidant (TAO) and 8-oxo deoxyguanine (8-oxo-dG) were detected in depressed disorder cases that treated with different medications included clomipramine, tryptizol, fluxetin, olanzapine, tryptizol with fluxetin, tryptizol with olanzapine and other types of …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 15, Issue 1, 2025 · pp. 41–47 Read article
-
AI and Machine Learning Approaches for Estimating Depression Severity: Techniques, Trends, and Applications
Abstract: Depression is a very common mental health disorder that results in a disorder of a person’s behavior, emotions, and cognitive abilities. Depression can be caused by environmental factors or hereditary factors. The person suffering from depression might have symptoms of suicidal thoughts, altering food patterns as well as sleeping issues. Depression is a global issue that has impacted millions of people globally having more effect on women worldwide. The complexity …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article
-
Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article
-
A Study and Prediction of Psychological Disorders Through Machine Learning
Abstract: Physical illness is very much visible but not psychological illness therefore, it requires more attention and care. Psychological disorders also known as psychiatric disorders refer to a wide range of conditions affecting a person’s thought process, leading to significant changes in the behavior of an individual. The most prevalent psychological disorders include depression, anxiety disorders, and post-traumatic stress disorder (PTSD). Symptoms of psychological disorders vary greatly but include common symptoms …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 32–38 Read article
-
AI-Driven Psychological Profiling on Social Media: Mechanisms, Ethical Breaches, and Regulatory Challenges in Data Inference
Abstract: This literature review examines AI-driven psychological profiling on social media, analyzing 21 academic studies that focus on machine learning techniques such as supervised learning, deep neural networks, sentiment analysis, and natural language processing. These methodologies infer mental health indicators—such as depression, anxiety, and stress—from users' digital footprints, encompassing linguistic patterns, engagement metrics, and temporal behaviors. While these tools offer potential for early detection of psychological distress, they also raise significant …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 1–7 Read article
-
Role of a Nurse in Addressing Mobile Addictions
Abstract: Nurses are essential in recognizing, evaluating, and addressing mobile addiction by using their skills in thorough screening and assessing patients' histories. Through keen observation and structured assessments, nurses can detect signs of mobile addiction, such as social withdrawal, disrupted sleep patterns, and neglect of personal responsibilities. It is crucial to establish this initial identification promptly to begin timely interventions and provide necessary support to those affected. Patient education stands at …
Published in Journal of Nursing Science & Practice · Vol. 14, Issue 3, 2024 · pp. 25–29 Read article
-
Designing and Developing a Cancer Chatbot in a Website
Abstract: Cancer is a disease that affects millions of people worldwide each year and is characterized by the rapid growth of cells that are abnormal. The outcome is affected since numerous cases are discovered at advanced stages of the disease. Anxiety and depression are two mental health issues that frequently coexist with the illness, worsening its effects on sufferers. There were many medical apps that provide guidelines for patients, but these …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 1–9 Read article
-
Need of a Comprehensive and Feasible Psychometric Test in the Assessment of Perinatal Mental Health - A Systematic Review
Abstract: The perinatal period is a period of happiness as well as hardships. A woman undergoes many psychological changes during this period which makes her prone to mental health disorders that can be detrimental to the health of the women and her child. Its essential to detect these disorders as early as possible and hence a psychometric test or tool which is easy to administer and interpret is needed. Globally various …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 104–111 Read article
-
Awareness and Knowledge of Postpartum Psychosis Among Antenatal Women: A Call for Educational Intervention
Abstract: Postpartum psychosis (PP) is a rare yet critical mental health disorder that poses serious risks to the well-being of new mothers. This condition manifests through a range of acute symptoms, including manic episodes, depressive states, confusion, hallucinations, and delusions. Symptoms typically present abruptly within the first two weeks following childbirth, making it a medical emergency that necessitates urgent care. Left untreated, PP can lead to severe consequences, including self-harm or …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 125–134 Read article