Article Excerpt: Although researchers have made unprecedented progress in identifying ‘averaged’ or ‘population-level’ mechanisms of mental health disorders, these approaches have led to a drowning effect at an individual level where person-specific information is often lost if it doesn’t align with an averaged expectation. To bridge this gap between research and clinical practice, we have developed a novel individualised machine learning framework called Affinity Scores. By identifying personalised signatures that can be integrated into a clinician’s decision-making for each of their patients, Affinity Scores represent a fundamental shift in our approach to personalised psychiatry.
Full Article: https://tinyurl.com/mrcn2ayh
Article Source: Pursuit