Driving Knowledge to Action: Building a Better Future With Artificial Intelligence-Enabled Multidisciplinary Oncology.
Authors
Affiliations (7)
Affiliations (7)
- St Luke's University Health Network, Bethlehem, PA.
- Massive Bio, Inc, New York, NY.
- Lewis Katz School of Medicine at Temple University, Philadelphia, PA.
- Capital Health, Pennington, NJ.
- The University of Texas MD Anderson Cancer Center, Houston, TX.
- Emory University, Atlanta, GA.
- Quest Diagnostics, Secaucus, NJ.
Abstract
Artificial intelligence (AI) is transforming multidisciplinary oncology at an unprecedented pace, redefining how clinicians detect, classify, and treat cancer. From earlier and more accurate diagnoses to personalized treatment planning, AI's impact is evident across radiology, pathology, radiation oncology, and medical oncology. By leveraging vast and diverse data-including imaging, genomic, clinical, and real-world evidence-AI algorithms can uncover complex patterns, accelerate drug discovery, and help identify optimal treatment regimens for each patient. However, realizing the full potential of AI also necessitates addressing concerns regarding data quality, algorithmic bias, explainability, privacy, and regulatory oversight-especially in low- and middle-income countries (LMICs), where disparities in cancer care are particularly pronounced. This study provides a comprehensive overview of how AI is reshaping cancer care, reviews its benefits and challenges, and outlines ethical and policy implications in line with ASCO's 2025 theme, <i>Driving Knowledge to Action.</i> We offer concrete calls to action for clinicians, researchers, industry stakeholders, and policymakers to ensure that AI-driven, patient-centric oncology is accessible, equitable, and sustainable worldwide.