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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The Waiting Game of Ghost Networks in Behavioral Healthcare
There’s an unspoken game all the rage in behavioral healthcare–ghost networks. It is a silent crisis that is largely overlooked but causing real damage to families seeking care. Despite assurances that behavioral healthcare is accessible, these ghost networks make it nearly impossible to get the help we need. Two years ago, my family was hit…
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