Transforming radiology
worldwide with innovative AI

February 27, 2025 — Vilnius, Lithuania — Oxipit, a leading AI-driven healthcare technology company, has announced the appointment of Dr. Robert Epstein to its Radiology Advisory Board. His expertise in radiology and healthcare strategy will support Oxipit’s mission to enhance diagnostic workflows worldwide through trusted AI solutions, enabling faster, more precise diagnoses and advancing patient care.

Artificial intelligence is transforming industries worldwide, but nowhere is its impact more profound than in healthcare. As AI-driven automation advances, ensuring transparency, validation, accuracy, and implementation of AI ethical principles becomes paramount—especially in high-stakes fields like medical imaging.

February 17, 2025 — Geneva, Switzerland — Unilabs, a leading diagnostic services provider in Europe, announced the selection of AI solutions from Oxipit, a pioneering medical imaging AI company, to deploy solutions for chest X-rays throughout Unilabs’ European network. This partnership will see Oxipit’s AI solutions, ChestLink and ChestEye, integrated into Unilabs’ radiology workflows, streamlining chest X-ray reporting through automated triage and second-reading capabilities. The agreement covers the option to use these solutions within the entire Unilabs group in Europe, with the initial rollout starting in Portugal.

How can AI revolutionize radiology and address critical challenges in healthcare? In this compelling interview, Dr. Aditya Kale, a radiologist and medical algorithmic audit lead at University Hospital Birmingham (UHB), shares his experience leading the largest retrospective study in UK, which was conducted on Oxipit’s ChestLink AI solution. From tackling the NHS backlog in chest X-rays to redefining reporting efficiency and patient care, Dr. Kale unveils key findings and offers valuable perspectives on AI’s potential to transform radiology workflows. Dive in to discover the groundbreaking results, lessons learned, and what the future holds for autonomous AI in healthcare.

We reflect on the year Oxipit has had. Including experiencing significant growth in 2024, driven by the increasing demand for our autonomous AI solutions like ChestLink, ChestEye, and Quality, which help address the challenges of rising workloads and staff shortages in the radiology sector.

Leiden University Medical Centre (LUMC), a leading academic hospital in the Netherlands, faced the common challenges of increasing radiology workloads and the need for more efficient resource allocation. Like many healthcare institutions, LUMC realised that, despite being a tier 3 academic hospital, a significant percentage of specific radiological examinations showed no pathology findings, which represented a significant opportunity to optimise workflow and use its resources more effectively. For chest X-rays, one of the most commonly performed radiological examination, retrospective validation showed that between 40% – 50% of the X-rays contained no findings and thus could be characterized as normal X-rays.