AI in Cancer Care Supporting Patients Enhancing Vaccines and Predicting Risks
Experts at City of Hope, Simon Nazarian and Nasim Eftekhari, discussed the transformative potential of AI in cancer care.
Artificial intelligence (AI) is quickly transforming cancer care and improving not only clinical outcomes but also the emotional experience of patients and their families, according to experts at cancer research and treatment organization City of Hope.
Experts Simon Nazarian, system executive vice president and chief digital and technology officer, and Nasim Eftekhari, executive director of applied AI and data science, are at the front lines of this innovation, working to integrate AI into various aspects of oncology.
One of the main areas where AI is making a difference is in supporting patients through the emotional challenges of cancer.
Nazarian shared AI tools are being developed to help patients "access the right information at the right time," improving their overall experience throughout the cancer journey.
These tools use care coordination and provide essential emotional support during diagnosis, treatment and after treatment, ensuring that patients feel supported at every step.
AI is also playing a significant role in personalizing cancer treatments, particularly in the development of cancer vaccines.
Nazarian highlighted how AI’s ability to process vast amounts of data—from imaging to genomics—enables precision health.
By analyzing these data points, AI helps determine the most effective therapies tailored to individual patients, which leads to improving outcomes and improving the overall patient experience.
In addition, AI is being utilized to predict and prevent adverse events, such as sepsis, in cancer patients.
Eftekhari shared an example of how AI was used to create a predictive model for bone marrow transplant patients, who are particularly vulnerable due to their immunosuppressed state.
This model monitors vital signs, medications and other patient data to predict sepsis risk.
If a patient is deemed high-risk, clinicians are alerted and then execute proactive interventions.
She explained that this tool “predicts the risk of grade three complications,” helping doctors make more informed decisions to improve patient care.
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