| Hi, you are logged in as , if you are not , please click hereYou are shopping as , if this is not your email, please click hereEventsDescriptionTicket price: £15
Date and time:
15th April 2015, 10:00-16:00 Location:
C309/310, Tait Building
City University London, Northampton Square, EC1V 0HB For maps and directions please visit: http://www.city.ac.uk/visit  DescriptionLearning Outcomes By the end of this workshop, participants will be able to: - Describe the fundamental concepts of machine learning and distinguish them from traditional statistical approaches used in health research.
- Prepare and explore real-world clinical or public health datasets for machine learning analysis, including handling missing data and selecting relevant predictors.
- Apply common supervised machine learning techniques (e.g., logistic regression, decision trees, and random forests) to healthcare data using R/Python.
- Evaluate and compare machine learning models using appropriate performance metrics such as accuracy, sensitivity, specificity, confusion matrices, and ROC curves.
- Interpret machine learning outputs in clinically and epidemiologically meaningful ways to support evidence-based decision-making.
- Recognise key ethical, methodological, and practical considerations in applying machine learning within healthcare and public health settings, including bias, fairness, and explainability.
Ticket prices - City St George’s staff and students - £10.00
- External participants - £50.00
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