Life Sciences & Biotechnology
Title : | Artificial Intelligence Applications for Affordable and Accessible Healthcare for Differential Diagnostic of Psychiatric Disorders |
Area of research : | Life Sciences & Biotechnology |
Principal Investigator : | Dr. BHARTI , University Of Delhi |
Timeline Start Year : | 2022 |
Timeline End Year : | 2024 |
Contact info : | bhartirana.jnu@gmail.com |
Equipments : | Workstation with high computation capability
Servers with GPUs and adequate memory for AI/ML workloads |
Details
Executive Summary : | Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and schizophrenia (SZ) are psychiatric and neurodevelopment disorders. The prevalence of ADHD is 3-5% in school kids (http://pedneuroaiims.org/training_module_for_attention_deficit_hyperactivity_disorder.html) while the prevalence of ASD is 1 in 189 in girls and 1 in 42 in boys (http://pedneuroaiims.org/introduction-to-autism.html). The studies showed that psychiatric disorders are more observed in boys than in girls. Also, the number of ADHD or ASD patients is increasing. Further, the symptoms of ADHD and ASD are overlapping and may cause misdiagnosis. This scenario raises an alarming situation and demands an early, accurate diagnostic and monitoring system. Currently, the diagnosis is carried out using behavioral traits tests by clinicians for diagnosis and checking the growth of the disease. These tests are questionnaire-based assessments and hence subjective in nature. Thus, a time-efficient and easily assessable method is a need of time to help clinicians for improved prognosis and diagnosis, and also for patients for a better life. During the last decay, clinicians started using neuroimaging technologies to get an insight into the neuronal changes in the brain. Further, it is desired to explore the artificial intelligence (AI) and machine learning (ML) techniques for the development of an automatic diagnostic system for psychiatric disorders. The key question is: Will the incorporation of AI and ML techniques aid robust analysis of data of psychiatric disorders and thereby allow automated diagnosis of psychiatric disorders? Hypothesis: AI/ML techniques for analysis of neuroimaging data of patients with psychiatric disorders are superior to the manual analysis techniques and hence will be more accurate in the diagnosis and characterization of psychiatric disorders. Application: The proposed diagnostic system will be helpful in the diagnosis of an individual. AI/ML techniques will aid in the accurate diagnosis of psychiatric disorders with non-invasive MRI data. It will be helpful for clinicians to identify the psychiatric disorder and hence, will assist in developing individual-specific diagnosis therapy. Overall, a robust, affordable and easily accessible healthcare diagnostic system based on AI/ML techniques will be helpful for clinicians in early and accurate diagnosis of ADHD and ASD. |
Total Budget (INR): | 32,75,221 |
Organizations involved