USING AI AND GENOMIC DATA TO IMPROVE EARLY DIAGNOSIS OF MENTAL HEALTH DISORDERS WHILE PROTECTING PATIENT PRIVACY

Abstract

Advancements in artificial intelligence (AI) and genomic science are transforming psychiatric diagnostics by enabling early and precise identification of mental health disorders. This study investigates how AI and genomic data can be integrated to enhance early diagnosis of psychiatric conditions—specifically depression, schizophrenia, and bipolar disorder—while ensuring strong safeguards for patient privacy. Employing a mixed methods design, the research combines quantitative surveys, regression analysis, and qualitative interviews to assess current AI diagnostic techniques, examine privacy-preserving strategies, and develop a balanced framework that aligns diagnostic accuracy with ethical data governance. Quantitative findings show that federated learning and data anonymization are highly valued by stakeholders for maintaining privacy without sacrificing diagnostic utility. Regression results highlight institutional policy awareness and technical privacy mechanisms as key predictors of perceived data security. Thematic analysis of qualitative data reveals critical dimensions of trust, transparency, algorithmic fairness, and the necessity for embedding privacy into AI system design. The study applies the Theory of Responsible Innovation as a guiding framework to integrate these findings into a conceptual model that supports responsible deployment of AI in psychiatric genomics. The results not only reinforce existing literature on the promise and challenges of AI in mental health but also highlight the need for inclusive, transparent, and ethically grounded technologies. This research contributes to a novel framework that can inform clinical practice, policy development, and ethical AI design, supporting a future of predictive psychiatry that is both scientifically effective and socially responsible. The study concludes with actionable recommendations for researchers, clinicians, policymakers, and AI developers.