He used Claude, an AI model, to integrate blood tests, scans, wearable data, and journals to inform treatment questions and later to interpret ambiguous post-treatment PET and MRI results, helping rule out false positives and thymus rebound as the cause of suspected active disease.

Two oncologists offered starkly different treatment paths: one recommended a lighter chemotherapy regimen with about 60% success, while the other proposed a more aggressive, continuous in-hospital regimen with around 85% success; after consulting 12 opinions, eleven favored the aggressive approach, which he pursued.

A health-conscious founder, Conno Christou, discovers an aggressive, fast-growing non-Hodgkin’s lymphoma behind his sternum after a routine health check-up revealed a mass following a workout.

Christou emphasizes the AI tool did not replace doctors but helped him ask better questions and access a comprehensive literature base, particularly valuable for a rare cancer that a single oncologist might rarely encounter.

Post-treatment, he reflects on inefficiencies in the medical system and plans to maintain a healthier work-life balance, including Sundays off, while continuing to run his AI-powered platform Keragon that automates administrative tasks for medical practices.

During six months of chemotherapy, Christou treated the process like building a company, using data-driven monitoring (wearables, biomarker data, symptom journals) and leveraging AI to synthesize results and guide decisions.

He remains open to helping others undergoing similar experiences and asserts that AI-assisted medical support is already usable today, not just in the future.

The final PET/MRI readings showed no active disease; thymus rebound was identified as the cause of earlier ambiguity, avoiding unnecessary radiotherapy.