Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Vats, Prashant; Kshirsagar, Pravin R.; Upreti, Kamal; Lalit, Keshav; Tak, Tan Kuan; Mahajan, Shubham Title A name given to the resource Behavioral Analytics for Predictive Modeling of Mental Health Disorders: A Review of Machine Learning Techniques and Challenges Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025;pp.376-381 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IC363308.2025.10957310" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IC363308.2025.10957310</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105003904087?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105003904087?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vats P., Manipal University Jaipur, Dept. of Computer Science and Engg, Jaipur, India; Kshirsagar P.R., J D College of Engineering &amp; Management, Department of Electronics &amp; Telecommunication Engineering, Nagpur, India; Upreti K., Christ (Deemed to Be University), Dept. of Computer Science, Delhi NCR, India; Lalit K., Manipal Institute of Technology, Dept. of Computer Science and Engg, Karnataka, Manipal, India; Tak T.K., Singapore Institute of Technology, Singapore; Mahajan S., Amity School of Engineering and Technology (ASET), Amity University, Gurugram, India Description An account of the resource Mental health issues, including anxiety, stress, and depression, may remain untreated until they escalate to a severe level. The issues significantly impact an individual's overall well-being and productivity. Timely identification is crucial for the effectiveness of both intervention and therapy. The application of machine learning techniques makes behavioral analytics a powerful tool for mental health disease prediction modeling. By analyzing behavioral data, this technology facilitates the early detection of various illnesses. This work aims to provide a thorough overview of the use of machine learning techniques, including models that employ Deep structured learning as well as both unsupervised as well as supervised learning, to behavioral data, including activity levels, speech patterns, and facial movements, in order to identify signs of mental health. The benefits and drawbacks of a broad range of machine learning algorithms are examined, with a focus on how these computer algorithms may be applied to identify patterns linked to illnesses like stress, anxiety, and emotional depression. This study looks into the problems that this business encounters as well. These difficulties include combining behavioral data with extra environmental issues and physiological features from the immediate surroundings, the necessity for large and diverse datasets, the need for security of information, and the capacity to understand models. 2025 IEEE. Subject The topic of the resource Anxiety; Behavioral Analytics; Convolutional neural networks (CNNs); Deep structured learning; Depression; Early Detection; Facial Expression Recognition; Long short-term memory (LSTM); Machine Learning; Mental Health Disorders; Predictive Modeling; Recurrent neural networks (RNNs); Speech Analysis; Stress Detection Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833152749-5; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online