posted on 2024-07-09, 08:46authored byJohn Kang, Kyle Lafata, Ellen Kim, Christopher Yao, Frank Lin, Tim Rattay, Harsha Nori, Evangelia Katsoulakis, Christoph Ilsuk Lee
Oncology is becoming increasingly personalised through advancements in precision in diagnostics and therapeutics, with more and more data available on both ends to create individualised plans. The depth and breadth of data are outpacing our natural ability to interpret it. Artificial intelligence (AI) provides a solution to ingest and digest this data deluge to improve detection, prediction and skill development. In this review, we provide multidisciplinary perspectives on oncology applications touched by AI—imaging, pathology, patient triage, radiotherapy, genomics-driven therapy and surgery—and integration with existing tools—natural language processing, digital twins and clinical informatics.
Funding
Rapid Applied Research Translation initiative (RARUR000125)
Cancer Institute NSW (2021/CBG003)
Artificial Intelligence for Improved Breast Cancer Screening Accuracy: External Validation, Refinement, and Clinical Translation