This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a primary care provider. We will follow the patient's journey from the lens of the data that are created at each encounter, which will bring us to a unique de-identified dataset created specially for this specialization. The data set spans EHR as well as image data and using this dataset, we will build models that enable risk-stratification decisions for our patient. We will review how the different choices you make -- such as those around feature construction, the data types to use, how the model evaluation is set up and how you handle the patient timeline -- affect the care that would be recommended by the model. During this exploration, we will also discuss the regulatory as well as ethical issues that come up as we attempt to use AI to help us make better care decisions for our patient. This course will be a hands-on experience in the day of a medical data miner.
À propos de ce cours
Nigam ShahAcademic Director, AI in Healthcare Specialization; Associate Professor
- 5 stars74,77 %
- 4 stars18,91 %
- 3 stars4,50 %
- 2 stars1,80 %
Meilleurs avis pour AI IN HEALTHCARE CAPSTONE
The quality of peer review exercises was good and the content of the reading material was well understood
I would have liked to see more hands on with users actually writing code in a notebook. The quizzes need to be verified because some answers may not be correct.
There are 9 peer review tasks, but they are not obligate ;)
I really enjoyed this course as it was applied learning of all I learned during the previous courses of the specialization.
À propos du Spécialisation AI in Healthcare
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