Rohan Ahmed


2024

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Project PRIMUS at EHRSQL 2024 : Text-to-SQL Generation using Large Language Model for EHR Analysis
Sourav Joy | Rohan Ahmed | Argha Saha | Minhaj Habil | Utsho Das | Partha Bhowmik
Proceedings of the 6th Clinical Natural Language Processing Workshop

This paper explores the application of the sqlcoders model, a pre-trained neural network, for automatic SQL query generation from natural language questions. We focus on the model’s internal functionality and demonstrate its effectiveness on a domain-specific validation dataset provided by EHRSQL. The sqlcoders model, based on transformers with attention mechanisms, has been trained on paired examples of natural language questions and corresponding SQL queries. It takes advantage of a carefully crafted prompt that incorporates the database schema alongside the question to guide the model towards the desired output format.