Bournemouth University

Master in Digital Health and Artificial Intelligence - Máster en Salud Digital e Inteligencia Artificial

Bournemouth University
  • Imparte:
  • Modalidad:
    Presencial en Dorset
  • Precio:
    Unlimited number of Scholarships available
    UK, CI and ROI students: £8,000-£12,000 for full-time study

    International students: £12,500-£16,500 for full-time study
  • Comienzo:
    Septiembre 2024
  • Lugar:
    Fern Barrow, Poole,
    Dorset (Bournemouth) BH12 5BB
    Reino Unido
  • Duración:
    1 Año
  • Idioma:
    El Master se imparte en Inglés
  • Titulación:
    MSc Digital Health and Artificial Intelligence

Presentación

Advances in Artificial Intelligence (AI), ubiquitous sensing and wearable technologies have rapidly led to their adoption in digital healthcare. Hospitals and healthcare industries are using AI to provide effective and smart solutions for patients care.

Requisitos

A Bachelors Honours degree with 2:2 in a required subject, or equivalent
Required subjects: Computer Science/IT, Engineering, Design, Health and Social Care, Medical Science, Psychology, Business, Law, Forensic Science or similar

International entry requirements
If English is not your first language, you will need to provide evidence that you understand English to a satisfactory level. English language requirements for this course are normally:

IELTS (Academic) 6.0 with minimum 5.5 in each component, or equivalent.

Objetivos

Research Methods & Professional Issues: This unit provides an overview of different research methods used to address scientific research questions. It covers aspects of research design, implementation and how they apply to solving digital health and artificial intelligence based challenges in a quantitative, qualitative or mixed fashion.
Foundations of Health Information Systems: This unit aims to help you learn the fundamentals of health information systems while introducing key concepts, principles, processes and related issues, and carrying out relevant activities in the analysis and design of health information systems. Further, the unit will cover health data generation, compilation, analysis, synthesis, communication and analytics. You will develop a good understanding of the legal and ethical framework surrounding the professional implementation of health information systems and use of electronic health data.
Artificial Intelligence: The aim of this unit is to provide you with an introduction to the first principles and techniques that are employed in the greater field and sub-fields of Artificial Intelligence (AI), together with the skills and knowledge required to employ AI techniques for solving real-world and synthetic problems.

You will approach AI from a Computer Science perspective, with focuses given to the challenges faced within the field, nature inspired algorithms, and their applications to complex real-world problems.

Accessibility & Assistive Technology: The aim of this unit is to provide you with an introduction to understanding diverse user ne

Programa

Core units

Research Methods and Professional Issues: This unit will provide an overview of different research methods used to address clinical research questions. It will cover aspects of research design and how they apply to the question being asked whether the approach is quantitative, qualitative or mixed methods.
Foundations of Health Information Systems: Health information systems serve multiple users for various purposes and they provide the underpinnings for health-related decision-making. This unit aims to help you learn the fundamentals of health information systems by introducing the key concepts, principles, processes and related issues, and carrying out relevant activities in the analysis and design of health information systems. The unit will also cover health data generation, compilation, analysis, synthesis, communication and analytics. You will develop an understanding of the legal and ethical issues surrounding the implementation of health information systems and the use of electronic health data.
Artificial Intelligence: The aim of this unit is to provide you with an introduction to the principles and techniques employed within the greater field and sub-fields of Artificial Intelligence (AI), and the skills and knowledge required to employ AI techniques to solve real-world and synthetic problems. We will approach AI from a computer-science perspective, with focus given to the challenges faced within the field, nature inspired algorithms, and their applications to complex real-world problems.
Accessibility and Assistive Technology: An introduction to the concepts of accessibility and assistive technology, exploring how technology can be used to support people with temporary, situational or lifelong disabilities by helping to overcome challenges to their self-care, educational, vocational and recreational independence. The aim of this unit is to provide you with an introduction to understanding diverse user needs, focusing on challenges caused by temporary, situational or lifelong disabilities. You´ll also gather the skills and techniques necessary to conduct foundational, user-orientated research with people who have disabilities to inform the design of assistive technology that can help overcome challenges during specific tasks. You´ll be trained in the ability to develop novel prototypes of inclusive assistive technology with an accessibility-first design philosophy combining advances in Human-Computer Interaction, Data, and AI.
Individual Masters Project: You will develop an understanding of the characteristics and implications inherent in the solution of a complex, real-world problem within the context of a substantial, independently-conducted piece of work.

Option units

Neuronal Analysis: This unit focuses on the study and application of data analysis techniques in neuroscience. Such algorithms are either adapted or specifically designed for analysing neuronal activity in physiological and pathological brain states. The mathematical modelling of basic neuronal functions over the last century, inspired the development of sophisticated parallel data processors that imitate biological neurons and networks to a certain degree. A successful example is the widely used family of deep learning-based approaches. In parallel, methods from e.g., computational statistics, dynamical systems, partial differential equations and more recently machine learning, feedback to the neuroscience field; and provided valuable insights in the understanding of the nervous system. This unit discusses state-of-the-art analytical tools for identifying normal and altered behaviour of neuronal activity at multiple spatiotemporal scales, their applications and current limitations.
Blockchain and Digital Futures: The objective of this unit is to develop your skills and knowledge about the Blockchain technology and its usage. The material, lectures and seminars includes defining the Blockchain technology, its business aspect, issues, objectives, and challenges, covering Blockchain horizontal and vertical scaling, key basics of cryptography required for understanding the Blockchain technology concepts, different cryptocurrencies, and their issues, challenges, and networks. The unit also covers a few data analysis-based Blockchain technology scenarios and case studies. The aim is to develop related skills and an understanding of critically evaluating the key issues, challenges, and existing solutions.
Persuasive Technology and Behaviour Change: This unit will focus on the use and design of Persuasive Technology (PT) denoting technology-assisted solutions for influencing the attitude and behaviour of individuals and groups. You will cover mainstream psychological theories of persuasion, influence, decision making and behaviour change besides their application on a wide range of domains including health, business and e-learning. We will also discuss the risks and ethical consideration of persuasion and essentials for informed decision making. Analysis and design methods for persuasive technology solutions will also be studied. Studied case studies include applications for encouraging the increase in physical activities, digital well-being, anxiety and stress management skills and sleeping quality. We will also discuss the use of PT in a business context such as increasing staff engagement, digital marketing, user retention and energy consumption reduction.
Smart Systems: Artificial Intelligence is being embedded in various systems and tools to achieve better decision making and more autonomy. The unit draws on a large spectrum of smart systems technologies. It covers basic as well as advanced topics with the goal of providing an overall introduction into these technologies.

Salidas profesionales

As a graduate of this course, you’ll be prepared to undertake employment positions such as AI Scientist, AI Product Director, Clinical AI Fellow and many more. You’ll also gain transferable technical skills, opening up a wide range of career opportunities in a variety of industries.

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