Fellowship Bio

Cardiothoracic radiologist with hands-on experience in AI development (MIDI regulatory approval) & deployment (chest X-ray triage). Eager to apply this dual perspective to impactful clinical AI projects that deliver real-world benefit to patients.

Fellowship Project

MIDI: A Clinical AI Project to Transform Radiology Workflows

King’s College Hospital NHS Foundation Trust

My project focused on MIDI, an innovative AI tool designed to support radiologists by detecting over 120 brain abnormalities on MRI scans—immediately after the images are acquired. The algorithm’s primary function is to classify each scan as “normal” or “abnormal”, allowing abnormal scans to be prioritised in radiology worklists. The goal is to accelerate diagnosis, reduce delays in patient care, and streamline scan reporting. Developed at King’s College London, MIDI has already secured significant government funding to support a nationwide NHS rollout and collect real-world performance data. However, it must first achieve UKCA regulatory approval before clinical deployment. During my fellowship, I helped drive MIDI toward this critical milestone by leading on the regulatory and clinical validation workstreams. My responsibilities included authoring key components of the project’s Quality Management System including the Clinical Evaluation Report, Instructions for Use, Product Label and Post-Market Surveillance Plan. I also contributed to planning for national deployment by conducting a competitor analysis and assessing integration requirements for vendor-neutral AI platforms. By the end of the fellowship, the team will have submitted all required documentation to the regulator. The next exciting phase, deploying MIDI across NHS sites and generating real-world evidence, will be taken forward by the next cohort of NHS Fellows in Clinical AI.

Fellowship Testimonial

One of the most valuable aspects of this fellowship was the opportunity to connect with other Clinical AI Fellows from across the country. These relationships offered real insight into the challenges and opportunities of deploying AI safely and effectively within the NHS. Being part of this network has broadened my understanding of the field and created a lasting professional support system. I can’t wait to see what they all go on to achieve in their careers! Another major highlight was gaining hands-on experience with the regulatory approval process for AI as a medical device. Learning how to navigate clinical validation, quality management systems, and compliance requirements was a steep but rewarding learning curve. I’m incredibly grateful to the MIDI team for their support throughout the process, and I look forward to applying these lessons in future roles. The fellowship has equipped me with the skills, insights, and connections to confidently pursue a future in clinical AI. I’m excited for the next chapter.