Applications, Challenges, and Future Perspectives of Artificial Intelligence in Psychopharmacology, Psychological Disorders and Physiological Psychology: A Comprehensive Review

Abstract

Artificial Intelligence (AI) is revolutionizing psychopharmacology and psychological research, enhancing diagnostics, treatments, and accessibility. This review examines AI's transformative role, applications, challenges, and future directions in these fields. AI tools improve diagnostic accuracy by analyzing brain imaging, health records, and behavioral data, enabling precise identification of disorders like depression and schizophrenia. Personalized medicine, powered by AI, predicts individual medication responses, minimizing side effects and optimizing outcomes. Innovative therapies, such as virtual psychotherapists and AI-assisted social robots, expand access to mental health care in underserved areas. AI in psycho-radiology leverages brain imaging for tailored interventions and treatment prediction, while wearable technologies and digital phenotyping enable real-time mental health monitoring and early intervention. However, challenges persist, including data privacy, algorithmic bias, ethical dilemmas, and regulatory hurdles, emphasizing the need for robust governance. Future advancements include refining diagnostics through machine learning and natural language processing and integrating collaborative AI models for holistic, personalized care. Ensuring ethical, transparent, and culturally sensitive applications is essential for trust and sustainability. This review aims to explore the transformative potential of AI in psychopharmacology and psychological research, highlighting its ability to revolutionize mental health care while addressing the challenges inherent to its adoption and implementation.

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