Artificial Intelligence and Digital Health MSc

    
This module delves deep into the intersection of biobanking personalised/precision medicine and digital health. You will gain an understanding of the principles and practices of biobanking and how digital tools and technologies are transforming its landscape. Emphasis will be placed on biobanking initiatives developed in the UK such as the UK Biobank, Genomics England and Our Future Health and how AI can be used to mine that knowledge. Within these biobanks, you will assess critical aspects of importance in your querying, access and integrity, together with interoperability, ethical considerations, and the role of digital health in shaping the future of healthcare provision and research.

Advanced and integrated analysis techniques are required in order to harness the potential of ‘big data’ to advance healthcare delivery. Therefore, the purpose of this module is to introduce you to the basic concepts of data science and to learn its application in healthcare. The main module objective is to aid you in understanding and implementing the computational methods that help in extracting insights from healthcare datasets and developing new diagnostic, prognostic, predictive, or monitoring
applications to address global health challenges.

This module teaches the principles and practice of research with a focus on study design and methods of data collection. It will show how these designs and methods can be applied to evaluation studies as well as to research. The module provides a supportive and intellectually challenging environment within which you will develop your knowledge, understanding and skills as a researcher.

This module will provide an overview of modern techniques in Machine Learning and Data Mining that are particularly customised for Data Science applications. You will be introduced to a range of toolkits, such as R and Python and they will explore the features and strengths of different machine learning and data mining methodologies using selected data sets related to specific public sector or businesses application domains.

This module allows students to hone their research skills by undertaking a substantial piece of research. Within this module, students will learn how to formulate a research proposal, investigate an appropriate research topic, keep research records, analyse the results of their research, discuss the findings with reference to previously published work, and convey the importance of their research through effective communication. The project proposed and undertaken must be commensurate with a master's level qualification and include rigorous and critical data analysis with a high level initiative. Students are expected to work largely independently, but within a team and with structured support given by the supervisors. Learning in this module is facilitated through theme-specific tutorials and interactive workshops, covering aspects such as research compliance, research sustainability, effective communication, and preparation for employment/ career development.

This module offers a comprehensive exploration of Big Data's challenges, encompassing its inherent volume, velocity, variety, and veracity. It sheds light on both traditional SQL and evolving NoSQL database architectures, emphasising their pivotal roles in the contemporary data landscape. The curriculum goes beyond technical facets, delving into the nuances of data governance, data quality, and the surrounding regulatory and ethical and EDI considerations that are paramount in today's digital age.

This module will explore topics in science communication and will help you to develop transferable skills and perspectives in the many ways that scientific knowledge can be disseminated. In relation to applied practice, the nature and means of human communication will be explored and assessed. Central themes include considerations of the purpose of science in society and the likely impact its findings and their communication have on human behaviour. This module is heavily focussed on interactive workshops, and includes training in science journalism, public speaking and presentations, online engagement, and TV and radio production.

This module covers the theoretical and practical aspects of data visualisation including graphical perception, dynamic dashboard visualisations, and static data ‘infographics’. Tools used include R and Tableau. The module prepares students for becoming data visualisation specialists.

An depth study on the scope of commercial biotechnology and starting and financing an operational company. The role of intellectual property protection, preparing a business plan and communicating business ideas, assessing projects, managing a company, and managing finances are all included, as well as how to comply with industrial safety legislation and regulatory requirements.

This module will introduce the theoretical and practical underpinnings of systems biology. The emphasis is on studies of entire systems assisted by the use of bioinformatics and how the knowledge from these may be applied to medicine. The module will examine databases and other resources as well as discuss key issues to the studies of entire systems.