Keyword: Digital Health

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.

ABSTRACT: Introduction: This study is aimed at assessing the operational efficiency of the admission department of the National Research Oncological Center (NROC) for the period from 2020 to 2024 with an emphasis on the impact of digitalization on patient management and workflow optimization. Telemedicine is a key tool for improving the availability and quality of medical care, especially for patients living in remote regions. In oncology, its importance is increasing due to the need for interdisciplinary interaction and quick routing of patients.
Methods: A retrospective analysis was conducted using internal hospital records, admission logs, and national healthcare regulations. Key performance indicators were assessed, including patient intake volume, processing time, and rejection rates. The impact of digital tools such as automated registration, routing algorithms, and remote clinical validation was examined.
Results: Patient visits increased from 5,664 in 2020 to 11,851 in 2024, while cancer-related hospitalizations rose from 1,477 to 6,102. The average waiting time for reception was reduced from 12 to 7 hours, and the processing time for documentation was reduced from 45 to 15 minutes. The introduction of digital solutions improved the accuracy of admission and reduced the number of inappropriate hospitalizations. Improvements in identifying clinical contraindications and infectious risks through remote screening technologies were also noted. The number of telemedicine consultations increased 3 times, especially in surgery and transplantology.
Conclusion: Digital transformation has significantly improved admissions efficiency, improving patient flow, reducing processing time and improving decision-making. Further development of digital infrastructure and staff competencies is recommended to ensure sustainable growth and quality of care in cancer care. The comprehensive implementation of telemedicine and interaction with air ambulance contribute to increasing the availability of cancer care, optimizing resources and reducing costs.