Baptist Health Herbert Wertheim Cancer Institute is using a new artificial intelligence platform, Eon, to help patients receive timely follow-up care after imaging exams. The system reads radiology reports and pulls data from electronic medical records to catch incidental findings-unexpected discoveries that might need additional attention-so care teams can act sooner and more consistently.
How the platform identifies patients who need follow-up
Eon reviews the full text of radiology reports and cross-references the electronic medical record to flag certain incidental findings. The tool currently focuses on lung and pancreas findings. Plans call for expanding to breast, thyroid, kidney, and liver findings in the future. Incidental findings are abnormalities that appear during an exam done for an unrelated reason, and the technology helps care teams spot them without manually scanning every report.
"This technology is set to advance our capabilities by helping us identify patients who may benefit from follow-up care sooner and more consistently," said Dr. Leonard Kalman, Acting System Chief Executive, Baptist Health Cancer Care, and Acting Executive Medical Director, Baptist Health Herbert Wertheim Cancer Institute. "It supports our commitment to early detection, providing coordinated, timely care and helping patients receive the right care at the right time."
Flagging by level of concern
The platform organizes findings by urgency so care teams can decide the most appropriate next steps. Findings that may need faster attention are flagged through existing processes at the Institute. Other findings are monitored through the software, with follow-up scheduled as needed. Both the patient and the ordering physician receive the information, and the physician can choose to manage follow-up directly based on the patient's individual needs.
The use of AI-enabled platforms like Eon reflects a broader shift in AI for Healthcare, where technology assists clinicians rather than replacing their judgment. Baptist Health emphasized that the tool supports physicians and care teams by helping them review information more efficiently, but it does not make clinical decisions. Physicians and care teams remain at the center of all medical decision-making.
Why this matters for healthcare and IT professionals
For healthcare teams, the platform reduces the risk of missed incidental findings and streamlines the follow-up process, which can lead to earlier interventions. IT and development professionals working in health systems will see a real-world example of an AI system that integrates with existing EMR and radiology report workflows, using natural language processing to extract actionable items from unstructured text. The expansion plan to other organ sites signals that the architecture is designed to scale across multiple clinical areas, offering a model for building modular, specialty-specific AI tools within a single platform.
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