Agentic AI for Clinical and Patient insights

A leading hospital integrated Unique Computing's multimodal LLM to analyze EHR, voice, and imaging data, enabling physicians to access actionable insights instantly.

[ TIMELINE ]

7 months

[ CLIENT ]

Microsoft Azure (Healthcare APIs)

[ CHALLENGE ]

A regional hospital network struggled with fragmented patient records and delayed clinical decisions:

Physicians spent excessive time searching through unstructured electronic health record (EHR) notes, lab results, and imaging reports.
Clinical decision-making was delayed, leading to increased readmissions and diagnostic errors.
The lack of real-time risk assessment tools limited the ability to implement proactive interventions for chronic conditions.
Patient care teams lacked a unified view of medical history, behaviors, and care plans.

[ SOLUTION ]

Unique Computing deployed a multimodal Agentic AI solution to deliver real-time, context-aware patient insights by integrating text, audio, imaging, and signal data. Key components included:

Multimodal Data Fusion
AI models processed and combined structured EHR data with unstructured inputs like physician notes, vitals, and imaging — enabling a single unified patient profile.

LLM-Powered Clinical Q&A
Physicians used natural language queries to extract relevant history, labs, and risk indicators instantly — reducing time spent navigating siloed systems.

Risk Stratification Engine
Predictive models flagged high-risk patients using time-series vitals, prior admissions, and medication patterns — improving care coordination and reducing readmissions by 30%.

[ RESULTS ]