SBIR Phase II: Decision Support Language Model and Electronic Data Platform for Early Screening and Management

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a novel software technology platform integrating individual data with standardized health care data for providing timely information. The system aims to track and reduce severity and consequences of health conditions. This decision support tool integrates directly into existing electronic health record systems to enable earlier identification of at-risk individuals without disrupting existing current workflows. A successful deployment of this software has the potential to reduce diagnostic delays, improve referral accuracy, lower costs, and meaningfully improve outcomes. This Small Business Innovation Research (SBIR) Phase II project will develop and validate an artificial intelligence-enabled decision support tool to support identification and management of health conditions. The system delivers screening recommendations alongside transparent explanations combined with professional guideline-based data and recommendations. The research and development objectives include validating the system across different populations, integration into a widely used systems, testing its usability with current users, and evaluating its real-world performance. Anticipated results include demonstrated screening accuracy above ninety percent across multiple health conditions and successful integration into current workflows. The project will produce an artificial intelligence-enabled decision support platform ready for broader deployment across health systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.