Informed Clinical Decision Making using Deep Learning
About this course
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.
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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
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