Data Extraction to Identify and Analyze the Symptoms of Mental Illness
Thulasi Bikku, Arpit Kumar Jain, Ravindra Changala, K. Suresh Kumar, Bijesh Dhyani · 2025
The CRIS-CODE project proposes using NLP to extract severe mental disorder symptoms from clinical writing. This text is specially extracted from the Medical Record Interaction Search (CRIS). The development of an all-inclusive system for the efficient analysis of massive amounts of clinical data is probably the end goal of this research. The research reportedly uses interactive search features and innovative data extraction techniques made possible by natural language processing, according to the intellectual. Researchers and mental health practitioners might gain a lot from this project if it gives them a way to quickly extract useful symptoms from patient accounts. In the long run, this strategy has the potential to help improve severe mental disease research, treatment, and diagnosis. Create and test apps take data from standard mental health records to identify SMI symptoms via the Clinical Information retrieved from the Record Interactive Search (CRIS) database; details on their distribution throughout a database of discharge summaries.