Want to keep learning?

This content is taken from the The University of Manchester & Health Education England's online course, AI for Healthcare: Equipping the Workforce for Digital Transformation. Join the course to learn more.

Skip to 0 minutes and 4 secondsThe world's most valuable resource of our century is not gold, nor oil, but data. Data is everywhere. It runs businesses, touches lives, and has the power to change the world. But how is health care utilising this power force? The health care industry faces multiple challenges, ranging from new disease outbreaks to maintaining optimal operational efficiencies. Can data solve these health care challenges of our time? In this week, we'll explore a range of case studies demonstrating examples of how artificial intelligence has been used in health care settings.

Skip to 0 minutes and 39 secondsWith the vast amount of data available in the health care sector, like financial, clinical, administration, and operational data, artificial intelligence tools can derive meaningful insights to improve both the patient care and the operational efficiency of the sector. Most importantly, in this section, we highlight examples of how these powerful tools have been integrated within existing health care pathways, like cancer care, surgeries, bed management, and radiology. How can we embed artificial intelligence tools in health care settings and give the gift of time back to health care practitioners? Furthermore, we will investigate the importance of data within a machine learning workflow.

Skip to 1 minute and 22 secondsWe will experience that the better the quality of the data we use to train a machine learning algorithm, the better the result will be. Finally, we'll investigate possibilities for the future, and the use of vast amounts of data to realise digital transformation in health care. What does the future look like?

Welcome to week three

In this week, we explore the data lying within the diverse ecosystem of healthcare. We investigate the challenges of having untidy data that are not machine-readable and the effect on a ML workflow.

Furthermore, we dive into several case studies that describe how data is being used in current research projects that employ machine learning tools in the healthcare domain. Finally, we will take a look on what the future looks like and the frameworks already in place to help us achieve a better data quality and availability for AI.

Share this video:

This video is from the free online course:

AI for Healthcare: Equipping the Workforce for Digital Transformation

The University of Manchester