FIDI (Fundação Instituto de Pesquisa e Estudo de Diagnóstico por Imagem) is one of Latin America's largest radiology service providers, delivering more than 400,000 diagnostic studies each month across 90 sites in Brazil. In 2024, FIDI introduced Oxipit’s AI-powered chest X-ray support tool in emergency departments, where fast, consistent interpretation is critical and real-time radiologist input is not always available.

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.

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.