In this riveting interview, we have Dr. Marc Lanovaz, a University of Montreal professor at the forefront of integrating data science and machine learning in behavioral healthcare. We discuss the impact of cultural relevancy in behavior analysis, how machine learning can improve clinical decision-making in mental health, and a groundbreaking virtual reality application simulating the world from an autistic perspective. The discussion also delves into the utilization of machine learning in tracking and predicting behavior changes and workplace stress. Moreover, Dr. Lanovaz underlines the significance of reinforcement in behavior therapy and its potential in data-driven applications that could revolutionize behavioral science and mental health care.
Advancing Behavioral Healthcare through VR & Machine Learning: A Conversation with Dr. Marc Lanovaz
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5 ABA Parent Participation Success Factors
At its heart, behavior therapy is a family therapy – it requires parents to learn new parenting methods (like how to set up the house for safety, use less punishment, minimize exposure to unnecessary triggers, how to have successful outings, reduce dependence on screens, increase communication and understanding, and more). Caregivers, siblings, and other family…
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