Here we provide a breakdown of the complusory, optional and project modules on MRes Health Data in Practice, which constitutes the first year of the Health data in practice: human-centred science programme.
Back to the programme page
Credit value: 15 each
Students will come from a range of backgrounds. We want to encourage interaction, develop critical thinking skills, and facilitate successful choice of PhD topic and supervisor. The module will provide a broad understanding of PhD opportunities, the wide context of the programme and of science and research at Queen Mary and across our national and international networks.
Content: Introduction to four programme themes, historical and contextual perspectives, understanding the use of data and algorithms, ethics and law, user perspectives.
Delivery: Weekly seminar series in term one delivered by programme leads, other senior supervisors, and incorporating patient and public input. In the second term you will explore case studies using problem based learning methods which will involve you in working together as a group to develop and design research addressing health data in practice scenarios. In the third term, you will submit a PhD proposal for internal peer-review comprising a short review of relevant literature and the rationale and scope of your proposal: a panel, which will recommend your enrolment, will review this.
Assessment: You will prepare critical appraisal summaries of seminars and will be marked on your three best critiques.
This will comprise fundamentals of research design, and qualitative and quantitative methods taken jointly with social science students. This module is divided into two components: research process (including methods and ethics) and basic statistics. You will learn about the research stages including conducting literature searches, setting research questions, selecting study designs and research methods, drafting research protocols and seeking ethical approval delivered in the form of lectures and practical seminars. The basic statistics component will introduce you to medical statistics and common statistical tests delivered in lectures.
Assessment: 75 per cent coursework, 25 per cent practical.
This research-led course introduces psychological theories of human communication to understand how technology can enrich and transform human interaction. It introduces the tools and techniques necessary for a principled approach to the design and evaluation of such technology.
Assessment: 80 per cent examination, 20 per cent coursework.
The main areas of study are (i) interaction and design (ii) modelling of interaction (iii) the design process (iv) design principles and (v) usability evaluation. Various types of interfaces are considered including those encountered on the web and mobile computing devices. A historical perspective is encouraged in order to provide a means of understanding current and projected developments in the discipline and profession of interactive computer system design. The module will include seminars and group laboratory classes in which analysis, design and evaluation methods will be used in practical contexts.
Assessment: 60 per cent examination, 40 per cent coursework.
This course will combine practical exploration of data mining techniques with an exploration of algorithms, including their limitations. Students taking this module should have an elementary understanding of probability concepts and some experience of programming.
Assessment: 70 per cent examination, 30 per cent coursework.
The aim of the module is to give you an understanding of machine learning methods, including pattern recognition, clustering and neural networks, and to allow you to apply such methods in a range of areas.
The module introduces you to techniques used in Artificial Intelligence including problem formulation, search, logic, probability and decision theory. The module aims to provide you with a basic knowledge of artificial intelligence; an understanding of how to design an intelligent agent; and knowledge of basic AI tools.
Assessment: 75 per cent examination, 25 per cent coursework.
Natural Language Processing (NLP) has become one of the most important technologies in Artificial Intelligence. Automatic methods for processing natural language now find application in almost every aspect of our communication in person or online, in particular through social media. The increased use of Neural Networks (NN) has played an important role in the most recent progress of NLP, as NN techniques have delivered improved performance in applications ranging from language modelling (next word prediction) to speech to machine translation to sentiment analysis. The proposed module introduces you to this cutting-edge approach to developing NLP systems.
This module provides a hands-on introduction to computer programming (popularly known as coding) using scripting languages popular in the field. The focus is on producing robust software for repeatable data-centric scientific work. Key programming concepts are introduced, and these concepts are then brought together in scientifically relevant applications to analyse data, interact with a database and create dynamic web content. Good coding practice, such as the importance of documentation and version control, is emphasised throughout.
Assessment: 100 per cent coursework.
This module covers essential theoretical notions of probability and the distributions of random variables which underpin statistical methods. It then describes different types of statistical tests of hypotheses and addresses the questions of how to use them and when to use them.
Assessment: 100 per cent examination.
This module introduces you to two of the most common study designs used in the evaluation of behavioural and organisational change. The module covers ethics, design, conduct, avoiding bias, process evaluations, and analysis.
Novel designs to maximise the use of health data to provide meaningful answers to important health and health service-related questions relevant to the effectiveness, cost-effectiveness and safety of interventions, including designs to evaluate data-driven technologies, and exploration of novel approaches to defining minimally sufficient data for evaluation.
This module introduces the principles of ethics, governance and regulation of biomedical research and new product regulation in global context, though with a particular focus on the legal implementation of these principles in the law of England and Wales.
Credit value: 45 each
The modules provide the opportunity to complete a substantial research project with a research group, focusing on one of the four themes. You will select from a range of projects. On completion of the projects, you will be able to: