Artificial Intelligence (AI) in Healthcare and Clinical Research
day1 – day2 Month 2025
Short Course
Course Description
Artificial intelligence (AI) has been used in a wide range of fields including in healthcare and clinical research. AI makes it possible to automate many tasks and analyse large quantities of information in health and clinical settings which would have taken a vast amount of time for researchers to handle. This course is designed for researchers interested in the application of AI methods in the conduct and statistical analysis of healthcare and clinical research. The course begins with an overview of AI and move on to specific AI methods and their practical applications using the R software. This 2-day course is a combination of synchronous lectures, tutorials and computer sessions with emphasis on the interpretation of outputs rather than writing computer codes.
Dates: To be announced (2 days in 2025)
Time: 9:30 – 16:30 GMT
Location: Online or possibly onsite at Newcastle University
Learning Outcomes
At the end of the course, participants should be able to:
1. understand the scope, terminologies and commonly used analysis in AI
2. differentiate machine learning and deep learning methods in AI
3. enumerate the applications of AI in healthcare and clinical research
4. explore datasets and tools used in AI in the context of healthcare and clinical research
5. implement machine learning algorithms using health data
6. explore examples of deep learning / neural networks
7. explain the practical challenges in developing, evaluating and implementing AI methods in healthcare and clinical research
8. discuss the ethical and regulatory consideration in using AI
Target Audience
The course is intended for applied statisticians and researchers who wish to understand the basics and use AI methods in the conduct and analysis of healthcare and clinical studies. Participants should have experience in doing basic statistical analysis and have knowledge of regression analyses and their computer implementation. Experience in using R software is useful, but not required.
Tentative Course Outline
The course will cover:
1. Introduction, terminologies and scope of Artificial Intelligence (AI)
2. Applications of AI in healthcare and clinical research
3. AI datasets and R
4. Machine Learning (ML) methods
5. Supervised Learning
6. Unsupervised Learning
7. Deep Learning / Neural Networks
8. Practical challenges in AI
9. Ethical and Regulatory Considerations in AI
Course Coordinator
Dr. Jingky Lozano-Kuehne, Newcastle University
Course Prerequisites
Participants will need access to a computer with installed R Software (version 4.2 or later (https://www.r-project.org/) and capable of video conferencing (in case the course is offered online).
Course Materials
Lecture handouts and instructions for the computer practical sessions will be made available during the course.
Course Fee
Details to follow in the registration invitation
Course Registration
It is important that you have access to the relevant computer resources and meet the prerequisites to ensure that you can benefit most from the course. The registration link will be posted here when the course is open for admission. If you have any question regarding the course, please contact the course coordinator at Email:jingky.lozano-kuehne@ncl.ac.uk.