PHILOSOPHY OF SCIENCE|EPISTEMOLOGY EXPLANATION CLASSIFICATION

In this module, students will examine some of the core topics in contemporary philosophy of science. There are three core themes: (1) What counts as scientific...

Knowledge, Explanation and Classification in Science (HPSC0085)

In this module, students will examine some of the core topics in contemporary philosophy of science. There are three core themes: (1) What counts as scientific knowledge. (2) What counts as a scientific explanation? (3) What role does classification play in science? These themes will be examined in the context of some working examples from scientific practice. These topics will be integrated with topics discussed in other modules, such as models, representations, mechanisms, causality and evidence.

ENVIRONMENT AND SUSTAINABLE DEVELOPMENT. PRACTICE. CORE. PRACTICE ENGAGEMENT

This module offers you a unique opportunity to be actively engaged in an action-learning platform, where knowledge and action are co-produced in collaboration...

Environment and Sustainable Development in Practice (DEVP0022)

The module aims to equip you to tackle a significant challenge in the application of artificial intelligence to healthcare data. You will demonstrate a sound...

Artificial Intelligence in Healthcare Group Project (CHME0039)

The module aims to equip you to tackle a significant challenge in the application of artificial intelligence to healthcare data. You will demonstrate a sound justification for the approach adopted as well as evidencing their originality (including exploration and investigation) and a self-critical evaluation of their solution’s effectiveness. You will develop a critical awareness of current problems and new insights in the field of artificial intelligence, as applied to healthcare, and  knowledge of developments in the domain.

By the end of the module you should be able to:

 identify the main approaches used in implementing machine learning algorithms in healthcare
	 understand the challenges involved in dealing with healthcare data, how is cleaned, curated and represented
	 design and implement a machine learning algorithm using the relevant software packages and techniques, including high performance computing hardware
	 plan and complete a project as part of a team
	 assess the statistical methods used in the evaluation of  machine learning in healthcare
	 apply approaches to optimizing and improving a machine learning algorithm
	 effectively summarise and present the findings of a machine learning project
You will report fortnightly on the progress made towards your final goal. You will make short presentations following an agreed format and receive verbal feedback on their progress.