AI for Comprehensive Solutions- Cross-Disciplinary Applications in Mental Health, Cardiovascular Detection, and E-Commerce

Authors

  • Dr. Mudassar Farooq Author
  • Dr. Mubashir Husain Rehmani Author

Keywords:

Artificial Intelligence, Mental Health, Cardiovascular Detection, E-Commerce, Healthcare, Machine Learning, Diagnostic Systems, Data Analytics

Abstract

Artificial Intelligence (AI) has rapidly evolved from a niche technological tool to a driving force across numerous industries, offering transformative solutions to longstanding challenges. This paper delves into AI’s cross-disciplinary applications, specifically focusing on its impact in mental health, cardiovascular health, and e-commerce. By combining AI’s power to analyze large datasets, recognize patterns, and make predictions, these fields are seeing groundbreaking improvements in diagnosis, treatment, and customer experience. In mental health, AI is helping detect early signs of conditions like depression and anxiety, providing immediate support through automated systems. In cardiovascular health, AI is enhancing diagnostic accuracy, enabling real-time health monitoring, and potentially saving lives by identifying risks before they become critical. Meanwhile, in e-commerce, AI is reshaping how businesses understand and engage with customers, creating highly personalized shopping experiences. This paper explores how AI’s integration across these diverse sectors not only improves outcomes but also builds a more interconnected and efficient future. Alongside these exciting advancements, it also addresses the ethical challenges and potential barriers to AI adoption, emphasizing the need for responsible development. By the end, we highlight how these interdisciplinary AI applications promise a more accessible, efficient, and insightful world for everyone.

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Published

2024-11-16

How to Cite

AI for Comprehensive Solutions- Cross-Disciplinary Applications in Mental Health, Cardiovascular Detection, and E-Commerce. (2024). AlgoVista: Journal of AI & Computer Science, 1(3). https://algovista.org/index.php/AVJCS/article/view/29

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