Beyond Imaging: Integrating LLMs into the Radiology Workflow

The next frontier of healthcare isn't just seeing, it's understanding. While traditional AI excels at identifying patterns in pixels, the future of radiology lies in the synthesis of visual findings and patient history.

The Hybrid AI Architecture

Nexus is currently pioneering an enterprise clinical intelligence platform that integrates Large Language Models (LLMs), specifically leveraging technologies like Med-Gemma and Gemini, to enhance diagnostic workflows. This "Multi-pathology" approach moves beyond standalone imaging to provide context-aware insights.

Enhanced Decision Support Features

• Context-Aware Interpretation By integrating clinical data such as patient age, smoking history, and chronic conditions (COPD, Asthma), the AI provides a more holistic assessment — going beyond what the image alone can convey.
• Automated Summaries The platform is evolving to support faster structured radiology reporting and automated clinical documentation, reducing the administrative burden on clinicians and accelerating report turnaround times.
• Explainable AI Our goal is to provide "explainable" outputs that assist clinicians in interpreting complex cases rather than acting as a "black box." Every AI finding is presented with supporting rationale that clinicians can evaluate and verify.

Why We Keep It in Beta

The decision to maintain these features in Beta is a deliberate clinical and regulatory choice. Multi-pathology classification — including lung cancer, silicosis, nodules, and fibrosis — and LLM-assisted reporting are internally validated but not yet covered by our CE MDR Class IIb certification. We are actively working to expand our regulatory coverage.

By clearly labelling Beta features, we ensure that clinicians understand the distinction between our certified screening capabilities and our emerging decision-support tools. This transparency is central to how Nexus approaches responsible AI deployment in healthcare.