This course is part of the AI in Healthcare Specialization

Matthew Lungren +4 more instructors

Offered By

AI in Healthcare SpecializationStanford University

About this Course

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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.
The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.  Visit the FAQs below for important information regarding 1) Date of original release and Termination or expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.

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Course 5 of 5 in the

AI in Healthcare Specialization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 11 hours to complete

English

Subtitles: English

Instructors

Instructor rating

4.8/5 (11 Ratings)

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 5 of 5 in the

AI in Healthcare Specialization

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 11 hours to complete

English

Subtitles: English

Offered by

Stanford University

The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is an American private research university located in Stanford, California on an 8,180-acre (3,310 ha) campus near Palo Alto, California, United States.

Syllabus - What you will learn from this course

Week

Week 1

2 hours to complete

Getting Started, Phase 1: Data Collection

2 hours to complete

2 readings

2 readings

Introduction10m

Phase 1: Data Collection10m

2 practice exercises

Phase 1. Project 130m

Phase 1. Project 230m

Week

Week 2

2 hours to complete

Phase 2: Model Training Part 1

2 hours to complete

1 reading

1 reading

Phase 2: Model Training, Part 120m

2 practice exercises

Phase 2. Project 130m

Phase 2. Project 230m

Week

Week 3

2 hours to complete

Phase 3: Model Training Part 2

2 hours to complete

1 reading

1 reading

Phase 3: Model Training, Part 215m

2 practice exercises

Phase 3. Project 130m

Phase 3. Project 230m

Week

Week 4

2 hours to complete

Phase 4: Model Evaluation

2 hours to complete

1 reading

1 reading

Phase 4: Model Evaluation15m

2 practice exercises

Phase 4. Project 130m

Phase 4. Project 230m

About the AI in Healthcare Specialization

Artificial intelligence (AI) has transformed industries around the world, and has the potential to radically alter the field of healthcare. Imagine being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed, as well as data outside the health system -- such as social media, purchases made using credit cards, census records, Internet search activity logs that contain valuable health information, and you’ll get a sense of how AI could transform patient care and diagnoses.

In this specialization, we'll discuss the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically. This specialization is designed for both healthcare providers and computer science professionals, offering insights to facilitate collaboration between the disciplines. CME Accreditation The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. View the full CME accreditation information on the individual course FAQ page.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
Is this activity accredited for Continuing Medical Education (CME)?
Dates and Duration
Original Release Date: 11/16/2020
Expiration Date: 11/16/2023
Estimated Time to Complete: 11 hours
CME Credits Offered: 11.00
Accreditation
The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. The Stanford University School of Medicine designates this enduring material for a maximum of 11.00 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.
Disclosures
The Stanford University School of Medicine adheres to ACCME Criteria, Standards and Policies regarding industry support of continuing medical education. There are no relevant financial relationships with ACCME-defined commercial interests for anyone who was in control of the content of this activity.
Will I earn university credit for completing the Course?
This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

More questions? Visit the Learner Help Center.

AI in Healthcare Capstone