Redefining Cancer Survivorship Care: How AI Technology and Big Data are Contributing to Proactive Care Delivery
https://news.med.miami.edu/ai-cancer-survivorship-risk-stratification/
Publish Date: 2026-05-26 08:00:00
Source Domain: news.med.miami.edu
- Researchers used AI methods, including machine learning and patient-reported measures, to identify higher risk of unplanned health care use and symptom burden for cancer survivors.
- The study highlights the potential of AI-enabled data analytics to support proactive risk stratification and survivorship care through the use of clinical and patient-reported data.
- It emphasizes the value of integrating novel methods combining medical, psychosocial oncology, and data sciences for improved long-term outcomes for cancer survivors.
- The research demonstrates that machine learning applied to survivorship data can identify survivors at increased risk for unplanned health care use and elevated symptom burden.
- The multidisciplinary study from Sylvester Comprehensive Cancer Center combines perspectives from clinical oncology, psychosocial oncology, population sciences, and data science to develop more proactive care strategies.
- It advocates for shifting from reactive to proactive survivorship care, using predictive signals generated from electronic health records and patient-reported data.
- The findings aim to align health resources earlier and more effectively by identifying patients at risk of struggle, potentially improving the quality and sustainability of long-term cancer care.
- Future research aims to refine and validate these AI models for broader cancer survivor populations and integrate them into the standards of survivor care practice.
