Revolutionizing Mental Health: Harnessing Predictive Analytics for Proactive Intervention and Support

EasyChair Preprint no. 12039

Abstract

This groundbreaking study explores the transformative potential of predictive analytics in the field of mental health, aiming to revolutionize traditional intervention strategies. Leveraging advanced algorithms and machine learning, our research focuses on the development of proactive measures to identify individuals at risk of mental health challenges before they escalate. By analyzing diverse datasets, including behavioral patterns, physiological markers, and digital interactions, we aim to create personalized risk profiles. These profiles enable early detection of potential mental health issues, allowing for timely and targeted interventions. The study also delves into ethical considerations, privacy safeguards, and the integration of AI-driven insights into existing mental health care frameworks. The findings highlight the promising impact of predictive analytics in reshaping mental health support, fostering a proactive and personalized approach to enhance overall well-being.

Keyphrases: Artificial Intelligence, early detection, Healthcare Transformation, mental health, Personalized interventions, Predictive Analytics, Proactive Intervention, Resilience

@Booklet{EasyChair:12039,
  author = {Asad Ali},
  title = {Revolutionizing Mental Health: Harnessing Predictive Analytics for Proactive Intervention and Support},
  howpublished = {EasyChair Preprint no. 12039},

  year = {EasyChair, 2024}}