In this video, Mariam Khayretdinova emphasizes the critical need to improve our approach toward mental health issues like Major Depressive Disorder (MDD), a leading cause of suicide. She notes the stark difference in the way we diagnose and treat physical versus mental health disorders, pinpointing the lack of hard data and biological tests in psychiatry as a significant barrier. The presentation highlights the heterogeneity of depression, which means it manifests differently in different individuals, requiring personalized treatment plans. It critiques the current ‘guessing game’ approach where patients have to go through various treatments before one works. Mariam points to technology, specifically AI and machine learning, as potential game-changers that could help to understand the complex nature of mental disorders. She suggests that we could utilize a variety of biological data, delivered through artificial intelligence and machine learning, for better understanding and personalized treatment.
She concludes with the possibilities of AI identifying different subtypes of depression, predicting treatment response, better understanding neurological and biological causes of depressive symptoms and ultimately preventing mental health disorders.
