Clinical AI

Introduction

The Clinical AI interest group seeks to bring together health professionals from diverse healthcare fields and data scientists who have a shared interest in clinical AI and to foster this network through interactive events on up-to-date developments in the field and cultivate innovative research projects.

Explaining the science

The clinical application of medical artificial intelligence is an area of mass interest to researchers, governments and industry and has the potential to improve clinical care. However, if this potential is to be realised, a substantial effort is required to up-skill the clinical workforce and to educate future generations of healthcare professionals in the development, application and pitfalls of clinical AI.

Aims

The Clinical AI interest group will address the following aims:

Sharing – To provide an incubator for clinicians and data scientists to share expertise in the design and methodology of clinical AI, share experiences of applying clinical AI and share in the collaborative, innovative application of AI in clinical practice.
Pooling – To draw together a community of AI-interested clinicians and health-interested data scientists. All interested parties are invited to apply with an aim to communicate and collaborate across disciplines. This pool of individuals will be encouraged to feed into the cross-sector activities of the health and medical sciences programme, offering unique insights from the clinical front line in terms of the opportunities and potential for AI to solve clinically important problems’.
Educating – To build training materials and facilitate educational events in order to educate AI-naïve clinicians and student healthcare professionals in the application of clinical AI. It is hoped that this double-impact approach will bring in those on the fringes and arm the next generation.

Talking points

What are the current examples of AI being used in clinical practice and is it supported by robust evidence?

Challenge: In recent times there has been an explosion in the development of AI algorithms for use in clinical practice. These may be undoubtably useful, but still require robust assessment and evaluation.

How could AI be used in the future to benefit clinical practice?

Challenge: With rapid developments in AI and the growth of their adoption in the clinical realm it is crucial to identify the future direction of travel and new areas of usage.

What are the ethical pitfalls in deploying AI in clinical practice and how can they be corrected?

Challenge: AI systems can learn and perpetuate existing biases within the health system and widen health inequalities. As more AI systems are developed and adopted, strategies need to be in place to ensure it benefits all patients and public, including those in minoritised and marginalised groups.

Supra-interest groups

We have formed supra-interest groups in different clinical specialties to bring together clinicians and AI experts in a more focused manner.

The current supra-interest groups are:

Anaesthetics and Intensive Care - led by Sandy Jackson, Lei Lu and Allan Pang.

The anaesthetics and intensive care supra-interest group focuses on all applications of AI around the time of surgery or other critical illness. These are data rich environments with both cost and complexity built in. These make them a prime target for clinical AI in numerous potential roles from closed loop systems to risk evaluation and the integration of novel sensors and monitoring. Get in touch if you are interested in hearing more or getting involved.

Medical Imaging and Computer Vision - led by Alexander Deng

The Medical Imaging and Computer Vision supra-interest group has a mission to feed its members’ curiosity.

This will take the form of live interactive debates on the most thought-provoking topics in this space, as well as case presentations from the front line of AI deployments in clinical workflows.

AI for Women's Health - led by Bianca Schor, Kristin Collett Caolo and Annalisa Occhipinti

The AI for women's health supra-interest group is an interdisciplinary community (e.g. clinicians, academics, data scientists, designers, health care professionals, students etc) interested in advancing women's health and how to leverage AI to do so.

The groups goals include:

Building an interdisciplinary and diverse community of individuals working or interested to work in women's health with (or without) AI
Bringing visibility to research on women's health and how AI can help to do so
Facilitating collaborations and bringing more people to the field
Offering relevant events & trainings, and sharing resources with the community

Pathology - led by Chris Banerji

Pathology is an extremely data rich clinical discipline spanning diverse modalities at multiple scales, from genomics and gene expression to cytology, tissue morphology and anatomy. This complex information is increasingly digitised (e.g., by whole slide imaging) and stored in large, often public repositories, paving the way for AI approaches to improve diagnosis, prognostication, treatment stratification and the health of our patients. This supra-interest group welcomes anyone interested in applying AI technologies to problems in pathology and overcoming the barriers to their clinical translation.

Public Health - led by Alisha Davies, Elliott Roy-Highley and Samantha Field

The Public Health supra-interest group focuses on the development and application of AI to prevent disease, prolong life, and promote, protect and improve health. The supra group enables sharing knowledge and ideas, pooling skills and learning across domain experts, data science and AI researchers, to advance the development of safe, ethical, responsible, and equitable AI across the three domains of public health.

NeuroAI - led by Jordan Tsigarides, Beatrice Panico, Danyal Khan

The NeuroAI supra-interest group seeks to celebrate, connect and catalyse innovations in artificial intelligence applied to neuroscience. It is an interdisciplinary collaboration spanning data science, computer science, the clinical neurosciences (including neurology and neurosurgery), neurotechnology, regulation and industry. Join us during our regular webinars, network events and collaborative database.

MSK AI - led by Nick Fuggle, Jordan Tsigarides, Meghna Jani, Salah Hammouche, Justin Green, Abhinav Singh, Luke Farrow and Samantha Cooray.

The MSK AI Supra-Interest Group is a vibrant community dedicated to advancing artificial intelligence in the field of musculoskeletal diseases. Our group fosters interdisciplinary collaboration, bringing together a diverse background of individuals including data science, computer science, rheumatology, orthopaedics, regulation, and industry. We aim to celebrate, connect, and catalyse innovative AI solutions for musculoskeletal health. Participate in our regular webinars and networking events (upcoming) to stay at the forefront of AI-driven advancements in this vital area.

How to get involved

Please complete the form below to join the Clinical AI Interest Group.

You can indicate your interest in one of the supra-interest groups on our membership form.

Once you have joined, you will be sent a monthly newsletter in which you can find out more about our activities and events, and you will be invited to join our slack workspace.

Click here to join us and request sign-up

YouTube playlist

Follow the link to access past seminars on the group's playlist.

The group also organised a summer school in July 2023. You can watch the presentations here.

Recent updates

We have started a Clinical AI Skills project - details can be found here: https://github.com/alan-turing-institute/Clinical-AI-skills

Organisers

Dr Nicholas Fuggle

Associate Professor at the MRC Lifecourse Epidemiology Centre (MRC LEC), University of Southampton and an Honorary Consultant Rheumatologist at University Hospitals Southampton