Diagnosis in Psychiatry with the Help of artificial intelligence

Background and aims: A crisis in psychiatry is a vital issue that separates psychiatry from medicine.The crisis in psychiatry is evident by many statistics with different competing approaches topsychiatric diseases, including psychodynamic, biological, molecular, pandemic, precise, cognitive,and phenomenological psychiatry, mind-brain dichotomy, and post-psychiatry. The purposeof this article is to explain the new nomothetic psychological approach (NNP) that uses machinelearning methods to build various diagrams by collecting risk, cognitive, and brain resilience.Method: We searched this topic in the reliable scientific database PubMed and summarized theresults of the articles using the keywords artificial intelligence, neuroscience, psychiatry, psychology,classification, machine learning, and deep learning, and using the filter, we reduced thenumber of reviewed articles to ۸ related to the topic.Result: This pattern recognition method exposes new categories of patients (transdiagnostic) andcan form new nosological categories (transdiagnostic).Conclusion: For the evaluation and general functioning of the brain in psychiatry, it is possible touse the information recorded and processed from brain signals, as well as the use of neuro markersusing image processing and machine learning. After the obtained information, data analysis onlatent variable scores of latent data R/R, AOP, cognition, brain some, and phenomena are applied.Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry(CP). By using artificial intelligence and using machine learning methods in psychiatry, errorscaused by misdiagnosis can be reduced. The incorporation of neural-based technologies intopsychiatry offers a novel means to use neural data in patient assessment and clinical diagnosis.