AI in cancer care: Promise, perils and the importance of ‘responsible use’
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The role of AI in oncology and hematology expanded dramatically in 2024.
Research continues to support its expanded use in diagnosis, staging and treatment decision-making.
With promise, however, comes the potential for misuse, privacy breaches and a depersonalization of care.
Healio is pleased to present the following updates from the past year related to use of AI in clinical settings to guide decision-making or improve outcomes.
1. An AI model classified risk for prostate cancer metastasis more accurately than standard guidelines, suggesting the approach could be used to reduce overtreatment or undertreatment. Read more.
2. The use of chatbot tools may be a valuable part of health management strategies to improve access to cancer genetic services. Read more.
3. A multi-institutional team of researchers developed an AI model designed to predict which patients with breast cancer are most likely to experience chronic pain. The model also may help clinicians address underlying conditions that contribute to risk for chronic pain. Read more.
4. An AI model revealed tumor size to be an independent factor when determining risk for prostate cancer recurrence or metastasis. Read more.
5. Most individuals with cancer who used an AI-based nutritional platform reported the application helped them regulate their diets and improved their quality of life. Read more.
6. The AI revolution has transformed delivery of cancer care; however, new challenges have emerged related to practical implementation and appropriate use. This Healio Exclusive provides insights into the complex issues oncologists are facing as they implement AI, as well as a series of core principles ASCO released to guide “responsible use” of AI. Read more.
7. The enthusiasm about AI in health care is accompanied by concerns about the risk for depersonalized care or privacy breaches. As clinicians and patients move together into uncharted territory, providers have the responsibility to explain and clarify the benefits and risks of AI to their patients, according to Gwen L. Nichols, MD, chief medical officer of The Leukemia & Lymphoma Society. “They need to be reassured that they have not become part of an algorithm, but rather that they are being looked at as an individual,” Nichols said. Read more.
8. An AI model may help identify children at higher risk for developing hospital-acquired venous thromboembolism. However, research into the viability of this approach identified barriers hindering implementation of this AI approach into practice. Read more.
9. An algorithm-based default referrals system led to a fourfold increase in specialty palliative care use when implemented in a large community oncology network, results of a randomized study showed. Researchers also noted less end-of-life chemotherapy use among patients who received the default palliative care referrals and died during the study. Read more.
To learn more about how artificial intelligence is being applied in clinical practice in oncology, hematology or other medical specialties, visit Healio’s AI in Medicine collection here.
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