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It will equip future health data scientists with the knowledge and skills to perform analyses and develop novel tools and methods for this rapidly growing field. It is aimed at students with diverse backgrounds from biomedical/medical domains, including clinical trainees, as well as computer science, mathematics and statistics to conduct their own analyses, and also to create the next generation of cutting-edge health data scientists who will be able to develop new tools and methods matching the latest technological advancements.
Students will learn about the breadth of health data science and its applications, and they will be taught how to design, perform and enhance analyses with the appropriate methods and technologies to address practical medical and clinical questions. Students will also benefit from training in areas such as clinical bioinformatics, health informatics, epidemiology, clinical systems, integrated multimodal data analysis and omics analytics for health data science careers in academia, industry and national health services.
Dr Andreas Karwath
Dr Karwath is an Associate Professor in the Institute of Cancer and Genomic Sciences and the deputy programme lead for the MSc in Health Data Science. His research interests focus on the integration of clinical data and the extraction of information and patterns from this combined information source using modern AI techniques, such as variational autoencoders (VAEs). He is also interested in cancer risk prediction, application of AI to Diabetes and clinical procedures, predictive toxicology, and the application of learning to rank, predictive toxicology.
View Dr Karwath's staff profile.
Professor Georgios V. Gkoutos
Professor Gkoutos is an Associate Director of Health Data Research UK and holds the chair of Clinical Bioinformatics, a joint appointment between the University of Birmingham Medical School and the University Hospitals Birmingham NHS Foundation Trust.
View Professor Gkoutos' staff profile.
Why study this course?
Students on the Health Data Science programme will:
- be embedded within a diverse, collaborative, interdisciplinary environment, incorporating academia, industry and healthcare.
- acquire skills in governing health data science, its foundations and effective application within healthcare settings.
- develop an in-depth understanding of healthcare systems, their underlying ethics and their governance structures. Students will also explore the role of current and potential future applications of health data science in the delivery of patient-centred care, patient-provider interactions and wider aspects of healthcare delivery.
- understand how health data science skills can revolutionise healthcare data and patient-specific genome information for research, clinical care and innovation in the 21st century.
- learn the value of different types of health information, systems and integration, and the role of information related technologies in delivering healthcare.
- gain practical experience of working within diverse, multi-disciplinary environments across the healthcare sector and its associated industries, and develop effective communication and delivery skills within the wider landscape.
- enhance their prospects. 80% of MSc Health Data Science students have received an offer for a PhD or job before finishing their thesis (2022).