The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
AI-Driven Early Detection of Mental Health Disorders Using Speech and Behavioral Patterns
Abstract
Early detection of mental health illnesses is vital to beat the disease and prevent deterioration; therefore, it is considered essential to the improvement of treatment outcomes. Over recent years, artificial intelligence has evolved into a powerful tool for early detection of mental health issues, often before any clinical diagnosis. This article looks at some AI-powered methods that analyze patients' speech and behavioral patterns with a view toward early diagnosis of mental health. These systems can pick up on very subtle cues that might signal the presence of disorders such as depression, anxiety, and PTSD, using machine learning models, NLP, and computer vision to analyze speech patterns, facial expressions, vocal tones, and even digital behaviour. There will be a discussion on how these AI technologies enable ongoing monitoring and early intervention in real-world contexts such as wearable technology, telemedicine, and mobile applications.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|