Community cancer centers treat 80% of American cancer patients but have up to 30% higher mortality rates than academic institutions. Kingsley Ndoh watched his aunt suffer through a late-stage colorectal cancer misdiagnosis in Nigeria, then discovered this disparity stems from resource constraints: community oncologists carry three times the workload with limited access to cutting-edge research and clinical trial results that academic centers implement immediately.
His solution: Hurone AI, a digital oncologist achieving 50% workload reduction and 95% protocol compliance. While competitors focus on diagnostics, Kingsley tackles the treatment decision gap with voice-activated data retrieval, real-time guideline updates, and treatment options backed by references. From piloting in Rwanda with Kinyarwanda language support to FDA approval for UCSF and Johns Hopkins, Kingsley reveals why international datasets reduce AI bias and how value-based care models are accelerating adoption of clinical decision support systems.
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Keywords: Hurone AI, oncology, clinical decision support, cancer care disparity, AI healthcare, FDA approval, value-based care, precision oncology, medical AI, global health equity