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.
In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. Visit the FAQs below for important information regarding 1) Date of the original release and expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.
Syllabus 5
Getting Started, Phase 1: Data Collection 2.5 hours
Phase 2: Model Training Part 1 2.5 hours
Phase 3: Model Training Part 2 2.5 hours
Phase 4: Model Evaluation 2.5 hours
Phase 5: Model Deployment and Regulation, Wrap Up 1.5 hours
Structured courses with graded quizzes, assignments and deadlines you can reset.
A shareable certificate from the university or company when you pay.
Financial aid is often approved for students in India (apply 15 days before you need it).
The actual Stanford lectures (CS229, CS224N, CS231N…): the deepest free material on AI anywhere.
Taught by Stanford University, one of the strongest names in its field.
Rated 4.7 out of 5 by 329 learners.
Self-paced: start any time.
A clear syllabus (5 parts) you can see before you start.
Disadvantages
Paid after a 7-day free trial (Coursera Plus or per course).
Some courses can be audited for free, but graded work and certificates need payment.
Graduate level: needs linear algebra, probability and programming first.
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Taught by
Matthew LungrenAssociate Professor, Department of Radiology
Nigam ShahAcademic Director, AI in Healthcare Specialization; Associate Professor, Medicine (Biomedical Informatics)
Serena YeungAssistant Professor, Biomedical Data Science
Tina Hernandez-BoussardAssociate Professor, Medicine (Biomedical Informatics), of Biomedical Data Science and of Surgery
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