Osterman, Travis

Abstract Artificial intelligence (AI) holds significant potential to enhance various aspects of oncology, spanning the cancer care continuum. This review provides an overview of current and emerging AI applications, from risk assessment and early detection to treatment and supportive care. AI‐driven tools are being developed to integrate diverse data sources, including multi‐omics and electronic health records, to improve cancer risk stratification and personalize prevention strategies. In screening and diagnosis, AI algorithms show promise in augmenting the accuracy and efficiency of medical image analysis and histopathology interpretation. AI also offers opportunities to refine treatment planning, optimize radiation therapy, and personalize systemic therapy selection. Furthermore, AI is explored for its potential to improve survivorship care by tailoring interventions and to enhance end‐of‐life care through improved symptom management and prognostic modeling. Beyond care delivery, AI augments clinical workflows, streamlines the dissemination of up‐to‐date evidence, and captures critical patient‐reported outcomes for clinical decision support and outcomes assessment. However, the successful integration of AI into clinical practice requires addressing key challenges, including rigorous validation of algorithms, ensuring data privacy and security, and mitigating potential biases. Effective implementation necessitates interdisciplinary collaboration and comprehensive education for health care professionals. The synergistic interaction between AI and clinical expertise is crucial for realizing the potential of AI to contribute to personalized and effective cancer care. This review highlights the current state of AI in oncology and underscores the importance of responsible development and implementation.

PURPOSE Multidisciplinary tumor boards (MTBs) support high-quality cancer care. Little is known about the impact of information technology (IT) tools on the operational and technical aspects of MTBs. The National Comprehensive Cancer Network EHR Oncology Advisory Group formed a workgroup to investigate the impact of IT tools such as EHRs and virtual conferencing on MTBs. METHODS The workgroup created a cross-sectional survey for oncology clinicians (eg, pathology, medical, surgical, radiation, etc) participating in MTBs at 31 National Comprehensive Cancer Network member institutions. A standard invitation e-mail was shared with each EHR Advisory Group Member with a hyperlink to the survey, and each member distributed the survey to MTB participants at their institution or identified the appropriate person at their institution to do so. The survey was open from February 26, 2022, to April 26, 2022. Descriptive statistics were applied in the analysis of responses, and a qualitative thematic analysis of open-ended responses was completed. RESULTS Individuals from 27 institutions participated. Almost all respondents (99%, n = 764 of 767) indicated that their MTBs had participants attending virtually. Most indicated increased attendance (69%, n = 514 of 741) after virtualization with the same or improved quality of discussion (75%, n = 557 of 741) compared with in-person MTBs. Several gaps between the current and ideal state emerged regarding EHR integration: 57% (n = 433 of 758) of respondents noted the importance of adding patients for MTB presentation via the EHR, but only 40% (n = 302 of 747) reported being able to do so most of the time. Similarly, 87% (n = 661 of 760) indicated the importance of documenting recommendations in the EHR, but only 53% (n = 394 of 746) reported this occurring routinely. CONCLUSION Major gaps include the lack of EHR integration for MTBs. Clinical workflows and EHR functionalities could be improved to further optimize EHRs for MTB management and documentation.