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New Innovation and Idea | Drug Discovery | United States of America | Volume 13 Issue 4, April 2024 | Popularity: 5.3 / 10
Empowering Medical Monitors: AI-Enabled Semantic Parsing for Enhanced Clinical Data Interpretation
Aditya Gadiko
Abstract: In the realm of clinical trials, the reliance on intricate coding for data analysis has long impeded the direct engagement of clinical professionals, such as Medical Monitors, with critical data insights. This study presents an innovative AI- based framework that utilizes semantic parsing to revolutionize data interpretation within clinical trials, effectively bridging the gap between technical execution and clinical expertise. Our approach, centered on a human-in-the-loop paradigm, enables non-technical subject matter experts to intuitively query data through natural language, which is then visualized through user- friendly UI components. This process not only encapsulates the intended inquiry but also allows for dynamic refinement by users to ensure accuracy and relevance. The introduction of this method significantly streamlines data analysis, reducing reliance on specialized programming skills and heralding a new era of data accessibility for clinical stakeholders. Through detailed case studies, we demonstrate the transformative impact of our approach, offering a glimpse into the future of clinical trials data analysis where efficiency, precision, and user engagement converge.
Keywords: Clinical Trials, Data Analysis, Analytics, Seman- tic Parsing, Artificial intelligence, Custom Listings, No Code, Natural Language Processing, Machine Learning, AI, NLP, ML, Human in the loop, HITL
Edition: Volume 13 Issue 4, April 2024
Pages: 136 - 142
DOI: https://www.doi.org/10.21275/SR24403035314
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