CDT Artificial Intelligence for Medical Diagnosis and Care

UKRI CDT- Artificial intelligence for Medical Diagnosis and Care

The aim of the CDT is to train a new generation of responsible researchers and innovators with the expertise and knowledge to transform the pace and precision of medical diagnosis and care through the application of Artificial Intelligence.

The CDT aims to create:

  • A sustainable and internationally outstanding Centre for research training in the application of AI to the early detection, diagnosis, treatment and care of cancer;
  • A research training environment with exemplary adherence to principals of equality, diversity and inclusion, targeting a 50-50 ratio of female to male graduates drawn from a broad range of health and STEM backgrounds;
  • National leadership in the development of software systems for ensuring security and privacy in the use of health-related data and compute-  intensive algorithms in the cloud;
  • Graduates who embody a culture of innovation and world class leadership, ensuring the UK remains at the forefront in health research, provision and commercial innovation;
  • Seeding of larger research collaborations with industry, the public sector and international university partners of the CDT;
  • Collaborative exploitation of new research ideas arising from the CDT in conjunction with industry partners, and technology transfer agencies.

Research themes

The research will span three themes where AI can be applied to advance cancer care and associated morbidities:

  • Screening and Early Detection: exploring the use of AI in epidemiology, risk stratification and digital phenotyping, to improve screening and prevention at scale; and developing AI algorithms to process multi-faceted patient data for early detection of cancer before normal symptoms present;
  • Diagnosis: exploring the use of AI to process data from pathology, radiology, wearable-sensors, patient records, and genomics, leading to faster, more precise and efficient diagnosis;
  • Therapy and Care: exploring the role of AI in the development of precision medications and novel therapies that meet the complex needs of individual patients; and improving the quality of life for patients living with and beyond cancer through development of automated decision support tools informed by self-reported patient outcomes and audio-visual recordings.

MSc programme

  • The MSc programme lasts the first 18 months.
  • It starts at the same time as, and takes place alongside, the PhD programme.
  • Students on the MSc programme gain strong support as a cohort.
  • Includes NHS staff induction and training for all students.
  • Students complete 180 Masters-level credits:
    • 60 credits covering the fundamentals of AI in the context of various application domains, including health;
    • 30 credits on the wider perspective of digital systems in the health service, and ethical and legal issues associated with health data;
    • 60 credits from over 100 potentially relevant modules according to your individual background and chosen PhD research topic;
    • A 30 credit research project.
  • Students will undertake a small research project in an area of AI in medical diagnosis and care to help understand how AI can support improvements in medicine.
    • The MSc project consolidates research skills to prepare students for the PhD programme and give them practical experience in developing and discussing AI solutions that have the potential to transform diagnosis and care.
    • Students will:
      • design, build and test an AI application using sample data
      • carry out a critical review of the relevant literature
      • demonstrate a clear understanding of the steps required to undertake research
      • present a coherent, conference-standard research paper and presentation
    • Students will present their projects at the CDT Conference Simulation.

PhD research

  • The PhD programme starts from month 6.
  • During months 6-18 the students undertake research alongside their MSc training.
  • At month 6, students select a topic area for their PhD research.
  • The research is jointly supervised by an interdisciplinary team involving both AI and clinical researchers.
  • The Student Page provides detail about our current students and their projects. Each year we seek projects from interdisciplinary teams to address key challenges in one of the CDT’s themes:
    • Screening and Early Detection
    • Diagnosis
    • Treatment and Care
  • The emphasis is on impact-driven research, innovation through application of AI, and experience/track record of the supervisory team. The topics offered are tailored to the interests of the students.

Research training

Alongside the MSc modules and PhD research, students follow an extensive programme of activities and events:

  • Participation in an annual CDT Conference, CDT seminar series, seminars in Leeds Institute for Data Analytics;
  • Participation in masterclasses organised jointly with The Alan Turing Institute, and annual Turing CDT conference;
  • Participation in joint events organised with other CDTs at the University of Leeds and nationally;
  • Training on ethics, responsible research and innovation, developing impact from research, and generic research skills;
  • Weekly participation in the CDT journal club and other relevant journal clubs;
  • Attending conferences and workshops at national and international level;
  • Participating in one outreach and public/patient engagement activity per year.

To read more about the programme visit UKRI Centre for Doctoral Training in Artificial Intelligence for Medical Diagnosis and Care (leeds.ac.uk)