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ONCOLOGY, NUCLEAR MEDICINE AND TRANSPLANTOLOGY
Review Article
Mar 28, 2026 1 1

Beyond Diagnostic Accuracy: Evaluating the Real-World Clinical Impact of AI-Enabled Radiology in Oncology and Nuclear

Oluwafoyinsola Ayobami Obilaja 1 * ,
Amarachukwu Jessica Okeke 2,
Chinedu Nwosu-Ijiomah 3,
Bolaji Mubarak Ayeyemi 4,
Albert Mensah 5
1 Department of Medicine, Clinical Sciences, University of East Anglia, Norwich, Norfolk, UK2 Department of Management Science, Stanton University, Garden Grove, CA, USA3 Department of Health Informatics, School of Computing, University of West London, UK4 Department of Computational Data Science and Engineering, North Carolina Agricultural and Technical State University, Greensboro, NC, USA5 Department of Radiography, University of Ghana, Accra, Ghana* Corresponding Author
Oncology, Nuclear Medicine and Transplantology, 2(1), 2026, onmt016, https://doi.org/10.63946/onmt/18258
Publication date: Mar 28, 2026
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ABSTRACT

Artificial intelligence (AI) has become increasingly integrated into radiology and nuclear medicine, particularly in oncology, where imaging plays a central role in diagnosis, staging, treatment planning, and response assessment. To date, evaluation of AI-enabled radiology has been dominated by diagnostic accuracy metrics derived from retrospective validation studies. While such measures are essential for technical assessment, they provide limited insight into real-world clinical value. High algorithmic performance does not necessarily translate into improved decision-making, workflow efficiency, patient outcomes, or health system performance. This narrative review critically examines AI-enabled radiology as a digital health intervention in oncology and nuclear medicine, emphasizing the need to move beyond accuracy-centric evaluation paradigms. We analyze the translational gap between controlled validation and routine clinical deployment, highlighting challenges related to dataset bias, generalizability, and human–AI interaction. Key domains of real-world impact are explored, including clinical decision-making, multidisciplinary integration, workflow and operational performance, patient-centered outcomes, and system-level implications. Methodological considerations for outcome-focused evaluation are discussed, alongside regulatory, ethical, and governance frameworks necessary for responsible implementation. We propose a clinical-impact–centered evaluation framework that links AI-assisted imaging to patient, clinician, and system-level outcomes within a continuous monitoring model. Reframing AI-enabled radiology as a clinical intervention rather than a standalone algorithm is essential for ensuring meaningful, equitable, and sustainable adoption in oncology and nuclear medicine practice.

KEYWORDS

Artificial Intelligence Radiology Nuclear Medicine Oncology Imaging Clinical Impact Digital Health Decision Support Systems Implementation Science

CITATION (Vancouver)

Obilaja OA, Okeke AJ, Nwosu-Ijiomah C, Ayeyemi BM, Mensah A. Beyond Diagnostic Accuracy: Evaluating the Real-World Clinical Impact of AI-Enabled Radiology in Oncology and Nuclear. Oncology, Nuclear Medicine and Transplantology. 2026;2(1):onmt016. https://doi.org/10.63946/onmt/18258
APA
Obilaja, O. A., Okeke, A. J., Nwosu-Ijiomah, C., Ayeyemi, B. M., & Mensah, A. (2026). Beyond Diagnostic Accuracy: Evaluating the Real-World Clinical Impact of AI-Enabled Radiology in Oncology and Nuclear. Oncology, Nuclear Medicine and Transplantology, 2(1), onmt016. https://doi.org/10.63946/onmt/18258
Harvard
Obilaja, O. A., Okeke, A. J., Nwosu-Ijiomah, C., Ayeyemi, B. M., and Mensah, A. (2026). Beyond Diagnostic Accuracy: Evaluating the Real-World Clinical Impact of AI-Enabled Radiology in Oncology and Nuclear. Oncology, Nuclear Medicine and Transplantology, 2(1), onmt016. https://doi.org/10.63946/onmt/18258
AMA
Obilaja OA, Okeke AJ, Nwosu-Ijiomah C, Ayeyemi BM, Mensah A. Beyond Diagnostic Accuracy: Evaluating the Real-World Clinical Impact of AI-Enabled Radiology in Oncology and Nuclear. Oncology, Nuclear Medicine and Transplantology. 2026;2(1), onmt016. https://doi.org/10.63946/onmt/18258
Chicago
Obilaja, Oluwafoyinsola Ayobami, Amarachukwu Jessica Okeke, Chinedu Nwosu-Ijiomah, Bolaji Mubarak Ayeyemi, and Albert Mensah. "Beyond Diagnostic Accuracy: Evaluating the Real-World Clinical Impact of AI-Enabled Radiology in Oncology and Nuclear". Oncology, Nuclear Medicine and Transplantology 2026 2 no. 1 (2026): onmt016. https://doi.org/10.63946/onmt/18258
MLA
Obilaja, Oluwafoyinsola Ayobami et al. "Beyond Diagnostic Accuracy: Evaluating the Real-World Clinical Impact of AI-Enabled Radiology in Oncology and Nuclear". Oncology, Nuclear Medicine and Transplantology, vol. 2, no. 1, 2026, onmt016. https://doi.org/10.63946/onmt/18258

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