The adoption of AI-powered digital health solutions in the treatment of cancer is shaping the oncology landscape by supporting earlier cancer detection and improving diagnostic precision throughout the patient care journey. As these solutions become increasingly integrated into routine clinical practice, they are expected to play a pivotal role in advancing the digital transformation of oncology and improving both clinical outcomes and healthcare system performance. Against this backdrop, the digital health market in Europe is expected to grow at a compound annual growth rate (CAGR) of 6% between 2025 and 2035, forecasts GlobalData, a leading intelligence and productivity platform.

GlobalData’s analysis reveals that Europe digital health market accounted for 7% of the global digital health market in 2025, reflecting the increasing integration of AI-powered devices and underscoring the expanding role of health tech in modern healthcare.

Against this backdrop, Median Technologies has recently announced that its AI-powered lung cancer screening software, eyonis LCS, has received CE marking as class IIb Software as a Medical device (SaMD) under the European Medical Device regulations. The approval follows the product’s US FDA clearance earlier in 2026 and enables its commercialization across the European Economic Area.

Shamreen Parween, Medical Devices Analyst at GlobalData, comments: “AI-driven software is increasingly enhancing clinical imaging by enabling more efficient and standardized image analysis. These solutions leverage advanced algorithms to identify imaging findings that might otherwise be overlooked, help clinicians improve diagnostic confidence, streamline reporting processes, and optimize patient management. While AI provides valuable analytical support, the final interpretation and treatment decisions remain the responsibility of healthcare professionals.

Eyonis LCS is designed to support lung cancer screening using low-dose computed tomography scans. It assists radiologists by automatically analyzing CT images to detect and characterize pulmonary nodules and estimates their likelihood of being cancerous using AI-based computer aided diagnosis.

Parween concludes: “The continued expansion of AI-enabled digital health solutions, supported by growing regulatory approvals, and sustained investment in digital health platforms, is expected to drive adoption across parts of Europe. These developments could further strengthen the role of digital health in enabling a more connected, data-driven, and patient-centric healthcare ecosystem.”