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Dissertation in Artificial Intelligence Enabled Healthcare (CHME0033)

Key information

Faculty
Faculty of Population Health Sciences
Teaching department
Institute of Health Informatics
Credit value
105
Restrictions
Only open to students on the MRes Artificial Intelligence in Enabled Healthcare programme
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

You will select a research project in artificial intelligence in healthcare at the start of the academic year and work with a supervisory team (including a clinician) to develop it and submit an outline proposal. Projects may involve the analysis of patient data, the implementation of novel software or the evaluation of an application. They should be at the level of an MSc project but wider in scope and will normally be capable of being developed into a PhD.

The module aims to provide you with a real extended experience of a substantial research project in artificial intelligence applied to healthcare and the opportunity to work independently, under the supervision of an academic team.

You will be able to choose from a wide variety of projects proposed by academics from different ¹û¶³Ó°Ôº departments including the IHI but also other clinical and engineering departments at ¹û¶³Ó°Ôº. Many projects will be conducted with our partners, including ¹û¶³Ó°ÔºH and Great Ormond Street Hospital taking advantage of the arrangements already in place to facilitate the appropriate ethical clearances required to access patient data.

You will explore, in depth, an aspect of artificial intelligence applied to healthcare. They will gain practical experience of some of the following: the collection of healthcare data, the analysis of healthcare data, the implementation of artificial intelligence software, the theory of artificial intelligence, and the evaluation of the impact of artificial intelligence.

You will attend workshops on responsible research and innovation and be able to discuss the ethical and societal issues raised by the use of artificial intelligence in healthcare, including consent and privacy issues around the use of patient data.

Module deliveries for 2024/25 academic year

Intended teaching term: Academic year (terms 1, 2, and 3) ÌýÌýÌý Postgraduate (FHEQ Level 7)

Teaching and assessment

Mode of study
In person
Methods of assessment
100% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
10
Module leader
Dr Ken (kezhi) Li
Who to contact for more information
aihealthcdt@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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