AI-supported Clinical Imaging Decision Support System

In November 2025, a team of students, researchers, and faculty at UMSN and SOCR developed, tested, and deployed a new sophisticated Clinical Imaging Decision Support System composed of two parts:

  1. A generation-3 Augmented Intelligent Agent (AIA-gen-3), which supports RAG AI-responses via custom-training and tuning pre-trained GAIMs and LLMs, and
  2. A generation-4 CLNQ, which facilitates highly accurate AI autonomous responses contextualized according to specific transfer-learning knowledge-bases. 

Driven by prompts from patients, clinicians, trainees, and other stakeholders, both AI systems are tested in describing, diagnosing, predicting treatment outcomes of simple ophthalmological images. These AI Clinical Decision Support Systems (AIA-gen-3 and CLNQ-gen-4) can be invoked in any modern browser. The AIA-3 sessions are virtual, confined to the browser tab, and no information is exposed to external AI API services. The CLNQ-4 also optionally utilizes API calls to external AI services. These sophisticated Clinical Imaging Decision Support Systems are developed by UMSN and SOCR scholars.


 

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