The article reviews the application of Machine Learning in diagnosing and assessing symptoms of schizophrenia. Initially, schizophrenia was a broad term for various severe mental health conditions, but now it’s diagnosed using a multitude of primary and secondary symptoms. The process of diagnosis can be time-consuming and subjective, hence the need for automated methods. Machine Learning, a dominant paradigm in Artificial Intelligence, has shown impressive capabilities across numerous domains, including medicine. It has great potential for healthcare professionals and patients alike, as it can lead to more consistent and accurate symptom estimation. The review focuses on methodologies that use Machine Learning for fine-grained estimation of schizophrenia symptoms.
Publication date: 26 Oct 2023
Project Page: Not provided
Paper: https://arxiv.org/pdf/2310.16677
