Cancer AI company integrates Mayo Clinic’s social determinants of health technology into navigation platform, seeking to enable personalized risk stratification
SEATTLE, WA, UNITED STATES, June 25, 2026 /EINPresswire.com/ — Hurone AI, a healthcare artificial intelligence company focused on cancer navigation, announced today that it has licensed Mayo Clinic’s HOUSES (HOUsing-based index of Socioeconomic Status) technology through a know-how agreement. This collaboration integrates Mayo Clinic’s validated social determinants of health measurement into Hurone AI’s governed cancer navigation platform, with the goal of enabling healthcare systems to deliver personalized, equitable care at scale.
The HOUSES index measures individual-level socioeconomic status based on housing characteristics and has been validated to predict more than 70 health outcomes1. By incorporating HOUSES into its platform, Hurone AI aims to enable cancer centers to identify patients at elevated risk for poor outcomes and proactively intervene with tailored support, such as addressing transportation barriers, financial assistance, nutrition access, and other social factors that impact cancer treatment adherence and outcomes by bridging the gap and connecting the patient with services to help meet these needs.
“Cancer outcomes are determined not only by biology and treatment, but by the social and economic circumstances patients navigate every day,” said Dr. Kingsley I. Ndoh, Founder and CEO of Hurone AI. “By collaborating with Mayo Clinic to integrate the HOUSES index into our platform, we aim to equip cancer centers with the clinical and social intelligence needed to deliver truly personalized, equitable care that recognizes the whole person, rather than just their condition. The intention is to provide actionable insights for every patient interaction that lays a foundation for personalized support that can lead to better health outcomes, regardless of social background.”
Hurone’s platform is designed to guide cancer patients through the complex journey from diagnosis through survivorship, providing real-time symptom management, treatment education, logistics coordination, and escalation to clinical teams when needed. By translating complex data into actionable empathy, Hurone AI’s goal is to ensure that every patient—regardless of their background—has a clear, supported path from diagnosis through survivorship.
This collaboration with Mayo Clinic is intended to give cancer centers the tools to close equity gaps, not just measure them. Hurone AI’s flagship product, Hurona, is deployed at leading academic medical centers where the platform is being integrated into clinical workflows to support thousands of cancer patients through their treatment journey. The company is measuring outcomes across patient experience, clinician efficiency, and healthcare utilization as part of its ongoing commitment to evidence-based care delivery.
Mayo Clinic has a financial interest in the technology referenced in this press release. Mayo Clinic will use any revenue it receives to support its not-for-profit mission in patient care, education, and research.
Mayo Clinic views artificial intelligence as a way to enhance the capabilities of clinicians, not as a substitute for their expertise, empathy, or judgment.
About Hurone AI: Hurone AI is a highly integrated AI-native navigation infrastructure for oncology, designed to extend the reach of clinicians beyond the four walls of the clinic. Built on a proprietary foundation of diverse clinical data and natively integrated into the Epic EHR, Hurone AI securely automates complex workflows and social risk stratification to improve patient adherence and outcomes. By deploying at top-tier research hospitals, Hurone AI provides the scalable data architecture necessary to solve health disparities and improve patient outcomes while reducing the administrative burden on oncology teams. For more information, visit www.hurone.ai.
1 – Kizilbash S, Wi CI, Amaral S, Beenken M, Watson D, McKinney W, Juhn Y. “Beyond biological risk: socioeconomic vulnerability and adverse pediatric kidney transplant outcomes.” Pediatric Nephrology. 2026 May 13. doi: 10.1007/s00467-026-07322-6. (Supplemental Digital Content, Appendix Tables 1 & 2) https://pubmed.ncbi.nlm.nih.gov/42126570/
Lisette Martje Rauwendaal
Hurone AI, Inc
press@hurone.ai
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