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.
What you'll learn
understanding of data mining in clinical databases
ability to apply deep learning in Electronic Health Records
knowledge of explainable deep learning models
insight into clinical decision support systems
awareness of ethics and fairness in AI in healthcare
Course objectives
to teach participants how to analyze and interpret clinical data
to develop skills in translating deep learning models into clinical applications
to foster understanding of the ethical implications of AI in healthcare