Dr. Benjamin P. Levy, clinical director of medical oncology at the Johns Hopkins Sidney Kimmel Cancer Center, said AI is bringing significant changes to cancer care and clinical trials. He spoke during the Chief Healthcare Executive Roundtable, a video series in which healthcare leaders discuss how technology is affecting their work.
Levy's assessment matches what many oncology teams are already seeing. Hospitals and research centers are testing AI tools that flag suspicious findings in scans, match patients to clinical trials, and summarize dense medical records. The work is practical: faster review, fewer missed matches, more time for direct patient care.
AI in the clinic
In cancer care, AI is most visible in diagnostic work. Algorithms trained on pathology slides and radiology images can highlight areas that need a clinician's attention. The technology doesn't replace the oncologist's judgment, but it changes how cases are prioritized and reviewed.
For healthcare professionals, the shift means learning to work with machine outputs rather than against them. AI for Healthcare covers these applications in medical settings.
AI in clinical trials
Clinical trials are another area of focus. Matching patients to studies is labor-intensive, and AI tools are being developed to scan eligibility criteria against patient records. The goal is to get the right patient into the right study sooner.
Research teams are also using AI to analyze trial data more quickly, spotting patterns that might otherwise take months to surface. AI for Science & Research tracks these developments.
Why this matters for healthcare professionals
Oncologists, nurses, and clinical research coordinators will increasingly be asked to act on AI-generated recommendations. That requires knowing what a model can and cannot do, and when to question its output. Levy's roundtable remarks suggest that skill is becoming part of the job description in cancer care.
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