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- Autorius: Anand Nayyar, Bandana Mahapatra, Suchit Mishra
- Leidėjas: Taylor & Francis Ltd
- Metai: 2026
- Puslapiai: 156
- ISBN-10: 1032568569
- ISBN-13: 9781032568560
- Formatas: 13.8 x 21.6 x 0.9 cm, minkšti viršeliai
- Kalba: Anglų
Mental Health Prediction using Machine Learning and Deep Learning Technology (el. knyga) (skaityta knyga) | knygos.lt
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Aprašymas
Today the integration of technologies like Machine Learning (ML) and Deep Learning (DL) are enabling us to understand, predict, and manage the rising mental health concerns better. This volume provides a comprehensive roadmap for researchers, practitioners, and enthusiasts to explore how artificial intelligence can revolutionize mental healthcare. The book delves into the cutting-edge innovations in predictive modeling, offering insights into how ML and DL algorithms can analyze complex psychological data, detect early warning signs, and predict mental health outcomes. Designed for a diverse audience, including data scientists, mental health professionals, and students, it combines technical rigor with real-world applications. With case studies, hands-on examples, and future-forward discussions, this book empowers readers to contribute to the next wave of mental health solutions powered by AI.
- Autorius: Anand Nayyar, Bandana Mahapatra, Suchit Mishra
- Leidėjas: Taylor & Francis Ltd
- Metai: 2026
- Puslapiai: 156
- ISBN-10: 1032568569
- ISBN-13: 9781032568560
- Formatas: 13.8 x 21.6 x 0.9 cm, minkšti viršeliai
- Kalba: Anglų
Today the integration of technologies like Machine Learning (ML) and Deep Learning (DL) are enabling us to understand, predict, and manage the rising mental health concerns better. This volume provides a comprehensive roadmap for researchers, practitioners, and enthusiasts to explore how artificial intelligence can revolutionize mental healthcare. The book delves into the cutting-edge innovations in predictive modeling, offering insights into how ML and DL algorithms can analyze complex psychological data, detect early warning signs, and predict mental health outcomes. Designed for a diverse audience, including data scientists, mental health professionals, and students, it combines technical rigor with real-world applications. With case studies, hands-on examples, and future-forward discussions, this book empowers readers to contribute to the next wave of mental health solutions powered by AI.
Atsiliepimai