Informed Clinical Decision Making using Deep Learning

This specialisation is for learners with experience in programming that are interested in expanding their skills in applying deep learning in Electronic Health Records and with a focus on how to translate their models into Clinical Decision Support Systems. The main areas that would explore are: Data mining of Clinical Databases: Ethics, MIMIC III database, International Classification of Disease System and definition of common clinical outcomes. Deep learning in Electronic Health Records: From descriptive analytics to predictive analytics Explainable deep learning models for healthcare applications: What it is and why it is needed Clinical Decision Support Systems: Generalisation, bias, ‘fairness’, clinical usefulness and privacy of artificial intelligence algorithms

• Extract and preprocess data from clinical databases
• Apply deep learning in electronic health records
• Impute missing data and encode electronic health records
• Design explainable, fair, and privacy-preserving clinical decision support systems

• Basic familiarity with the topic and terminology
• Readiness to engage in applied practical exercises