Şizofreninin Tanısında Yapay Zekanın Kullanımına Dair Derleme

This review examines the potential, application areas, and challenges of artificial intelligence (AI) in the diagnosis and management of schizophrenia. AI technologies such as neuroimaging, EEG, and natural language processing (NLP) have demonstrated high accuracy in early diagnosis and personalized treatment processes. Notably, AI has been effective in identifying biomarkers specific to schizophrenia and analyzing linguistic and cognitive abnormalities associated with the disorder. However, issues such as data privacy, ethical concerns, the risk of misdiagnosis, and limited sample sizes restrict the widespread clinical use of these technologies. The diagnostic accuracy of AI, its role in treatment planning, and the more precise analysis of neuroimaging data mark a revolutionary advancement in schizophrenia management. Nevertheless, for the effective use of these technologies, further studies with broader and more diverse sample groups are required, along with enhanced data security and ethical regulations. Additionally, training programs should be implemented to enable clinical personnel to effectively utilize AI-based systems, and multidisciplinary collaboration should be strengthened. Considering all these factors, enhancing the impact of AI in the diagnosis and management of schizophrenia should be prioritized. Keywords: Schizophrenia, Artificial Intelligence, Diagnosis.