Artificial intelligence fundamentals: A crash course for clinicians

Amadeus is a Data/Technology Lead in the NHS AI Lab Skunkworks team, working on accelerating the safe adoption of AI in the health and care system through practical knowledge and capability building. Before joining the Lab, Amadeus was Global Head of Product and CTO at Decoded, a leading technology education company. Amadeus combines his experience in the industry with a PhD in nanomedicine from the University of Oxford.

In the Skunkworks team, Amadeus has worked on the development of AI proof of concepts including predicting length of stay, bed allocation and CT registration and lesion detection.

Oscar Bennett is a Senior Data Scientist at Faculty where he works in the company's Health and Life Sciences division. Previously, he worked at Babylon Health in their Machine Learning R&D team and the NHS as a medical doctor and radiology speciality registrar.

At Faculty, he has worked with a range of clients in the healthcare, social care and biomedical science domains, including the NHS. His work has encompassed the development, validation and deployment of machine learning models as well as advising more broadly on data strategy across these domains.

He holds a Medical Degree and an MA in Natural Sciences from Cambridge University. He also holds an MSc in Medical Engineering and an MRes in Medical Imaging from UCL. He was awarded Membership of the Royal College of Physicians MRCP(UK) in 2018.

Chris is a medical doctor, having graduated from the University of Cambridge in 2017. He has experience applying data science and machine learning to healthcare and has a master's degree in Machine Learning.

He is passionate about education and shares educational content on YouTube and www.chrislovejoy.me

Jeff is an ophthalmologist who researches the interdependent factors that influence the implementation of clinical AI tools. He has spent much of the last year leading an NIHR funded evidence synthesis of all primary qualitative research into stakeholders’ perspectives on clinical AI implementation.

Dr Mike Nix is an AI researcher and Clinical Scientist in adaptive radiotherapy at Leeds Teaching Hospitals and the University of Leeds. He holds a joint fellowship with Health Education England and the NHS-AI lab investigating appropriate confidence and ethical implications for the use of AI in the clinic. He is particularly interested in uncertainty and risk quantification for robust and safe clinical decision making using algorithms, particularly the skills gaps and educational needs of the UK healthcare workforce in this area.