Best Practices for Data Management in Clinical Trials

Abstract

This study explores the potential of Lang Chain, a framework for constructing applications with advanced language models, to translate natural language queries into executable SQL code. Study propose an innovative Lang Chain-based architecture that receives a natural language query, analyzes it with a language model, and generates the corresponding SQL statement for database querying. This approach aims to empower non-technical users, facilitate inter-team collaboration, and enable data-informed decision-making. However, challenges persist, including managing complex queries and grasping domain-specific terminology. This research investigates the methodology and system design of our proposed natural language interface for databases, leveraging Lang Chain and extensive language models. Study also explore the possibilities and potential applications of this system, as well as future research avenues for enhancing its functionalities and addressing current constraints. By integrating advanced natural language processing with database technologies, this research aims to enable inclusive and powerful data querying experiences.