Generative AI in the Real World: Kingsley Ndoh on Improving Cancer Care with AI
Assisting Patients and Improving Clinical Trials
What can AI do to improve healthcare? Kingsley Ndoh, founder of Hurone AI, talks with Ben Lorica about how Hurone is making cancer care more effective for people who are underserved by the medical system. He discusses how AI can streamline the medical process, both helping doctors to treat patients more effectively and making clinical trials more diverse.
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About the Generative AI in the Real World podcast: In 2023, ChatGPT put AI on everyone’s agenda. In 2024, the challenge will be turning those agendas into reality. In Generative AI in the Real World, Ben Lorica interviews leaders who are building with AI. Learn from their experience to help put AI to work in your enterprise.
Timestamps
- 0:00: Introduction.
- 0:36: What motivated you to apply AI to cancer care? What problems are you trying to solve?
- 1:39: We need environments for training AI models that are effective for all populations.
- 2:31: Current oncology solutions serve advanced healthcare systems, leaving community oncology centers and international markets underserved.
- 3:32: What was the situation before Gukiza [Hurone’s app]? What does Gukiza enable today?
- 4:00: Gukiza makes care more accessible to patients and optimizes workflows for oncologists. They may have to travel long distances to see an oncologist; they may have side effects or even emergencies that are avoidable; data about events may be lost.
- 7:10: Gukiza streamlines the process; it’s a two-way system that can be used standalone. There is a HIPPA-compliant API that can be integrated into major electronic medical records systems. Patients aren’t limited to an app; there is an API for WhatsApp, Telegram, and text messaging.
- 8:29: Patients can describe their problems. Clinicians can click a button and generate a response that they can review and send to the patient. Clinicians can also call patients, do clinical summaries, and see how patients are progressing.