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AI in Healthcare Capstone
Coursera
Course
Unknown

AI in Healthcare Capstone

Stanford University

A capstone project applying healthcare AI concepts to EHR and imaging data to build models that support patient risk stratification decisions.

Unknown5 weeksEnglish22,213 enrolled

About this Course

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

What You'll Learn

  • Analyze EHR and medical imaging datasets
  • Build models for patient risk stratification
  • Evaluate models using different feature and validation choices
  • Assess how patient timelines affect care recommendations

Prerequisites

  • Basic computer and internet skills
  • Ability to follow course materials in English

Instructors

M

Matthew Lungren

Associate Professor

N

Nigam Shah

Academic Director, AI in Healthcare Specialization; Associate Professor

S

Serena Yeung

Assistant Professor

T

Tina Hernandez-Boussard

Associate Professor

Topics

Health Informatics
Health
Responsible AI
Performance Tuning
Machine Learning Software
Artificial Intelligence
Health Care Procedure and Regulation
Model Evaluation
Risk Modeling
Model Deployment

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

المعلوماتية الصحية
السجلات الصحية الإلكترونية
تعلم الآلة
تقييم النماذج
الذكاء الاصطناعي المسؤول
تحليل الصور الطبية
Health Care Procedure and Regulation
Model Evaluation
Risk Modeling
Model Deployment

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