About this event

  • Date and time Fri 22 Apr 2022 from 9:00am to 2:30pm
  • Location Online
  • Organised by Digital Health

AI Fundamentals is a one-day virtual event that will provide clinicians with the tools needed to understand Artificial Intelligence in healthcare. It is designed by the RSM’s Digital Health Council, which has developed a strong reputation for delivering high-quality AI events over the past three years.

The course is tailored for clinicians of all grades with little to no experience of artificial intelligence or machine learning and looking for an accessible introduction to the topic. It will be delivered by a faculty of experts that will guide attendees through five high yield domains all clinicians should be familiar with.  

This webinar will provide clinicians with a cohesive primer on AI in healthcare delivered by an expert faculty. By the end of the course, attendees will be able to:  

  •  Describe common applications of AI in healthcare  
  •  Explain the key steps in the validation of AI models   
  •  Confidently appraise and analyse AI-based research   
  •  Identify the ethical and technical barriers to developing AI models   
  •  Discuss some of the legal and regulatory aspects of AI in healthcare

This webinar is available for on-demand viewing. The webinar recording will be available for registered delegates up to 60 days after the live webinar broadcast. The link will be sent 24 hours after the webinar takes place. 

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Key speakers

Dr Amadeus Stevenson

Dr Amadeus Stevenson

Data/ Technology Lead, NHS Artificial Intelligence Lab Skunkworks Team

Speaker's biography

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.

Dr Oscar Bennett

Dr Oscar Bennett

Senior Data Scientist, Faculty

Speaker's biography

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.

Dr Chris Lovejoy

Dr Chris Lovejoy

NHS Clinical Entrepreneur, NHS England and Machine Learning Engineer

Speaker's biography

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

Dr Jeff Hogg

Dr Jeff Hogg

National Institute for Health Research Doctoral Fellow, Newcastle University

Speaker's biography

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

Dr Mike Nix

Clinical Scientist, Radiotherapy Physicist, Topol Digital Health Fellow, Leeds Teaching Hospitals NHS Trust

Speaker's biography

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.

Agenda

View the programme

Artificial intelligence foundations

Dr Amadeus Stevenson, Data/ Technology Lead, NHS Artificial Intelligence Lab Skunkworks Team

Comfort break
How to build an artificial intelligence model (building training and validation)

Dr Oscar Bennett, Senior Data Scientist, Faculty

Comfort break
How to read an artificial intelligence paper

Dr Chris Lovejoy, NHS Clinical Entrepreneur, NHS England and Machine Learning Engineer

Lunch
How to make artificial intelligence work for everyone

Dr Jeff Hogg, National Institute for Health Research Doctoral Fellow, Newcastle University

Comfort break
How to use artificial intelligence in clinical decision making

Dr Mike Nix, Clinical Scientist, Radiotherapy Physicist, Topol Digital Health Fellow, Leeds Teaching Hospitals NHS Trust

Location

Online

Disclaimer: All views expressed in this webinar are of the speakers themselves and not of the RSM.

Registration for this webinar will close 1 hour prior to the start time. You will receive the webinar link 1 hour before the meeting. Late registrations will not be accepted.