Artificial intelligence (AI) is rapidly reshaping the future of cancer care, but such dramatic innovation also brings important questions.
AI has evolved from early consumer tools (like autocorrect on phones, customer service chatbots, and personalized shopping recommendations) to advanced systems with the potential to revolutionize biomedical discovery and patient care. While there is tremendous excitement around AI, there is also a critical need to use it responsibly.
Researchers are actively studying how to implement AI across the lung cancer continuum. Key areas of focus include improving early detection, predicting immunotherapy effectiveness, and matching patients to clinical trials. By integrating pathology, imaging, genomics, and electronic medical record data, AI holds promise for improving lung cancer care in ways we couldn’t even imagine five years ago.
At the same time, experts advise us to be cautious. AI models are computer systems that learn patterns from examples and then use those patterns to answer questions or perform tasks. Therefore, poorly trained models or models applied outside the populations they were trained on can lead to inaccurate recommendations, and sometimes, unintended harm to patients.
Today, AI is already supporting clinicians through ambient notetaking and workflow support. Looking ahead, the future may include the first AI-driven biomarker for lung cancer and more precise, patient-centered care.
In a recent conversation at LUNGevity’s International Lung Cancer Survivorship Conference, our own Brittany McKelvey, PhD, welcomed Sandip Patel, MD, Professor at the UC San Diego Moores Cancer Center, to explore how AI is delivering real value in lung cancer care, where caution is needed, and what the future may hold. Watch the recorded discussion below.