Evaluations of AI Applications in Healthcare
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Evaluations of AI Applications in Healthcare
This course is part of AI in Healthcare Specialization
27,394 already enrolled
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341 reviews
341 reviews
What you'll learn
Principles and practical considerations for integrating AI into clinical workflows
Best practices of AI applications to promote fair and equitable healthcare solutions
Challenges of regulation of AI applications and which components of a model can be regulated
What standard evaluation metrics do and do not provide
Details to know
22 assignments
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There are 8 modules in this course
With artificial intelligence applications proliferating throughout the healthcare system, stakeholders are faced with both opportunities and challenges of these evolving technologies. This course explores the principles of AI deployment in healthcare and the framework used to evaluate downstream effects of AI healthcare solutions.
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's included
10 videos2 readings3 assignments
10 videos•Total 30 minutes
- Learning Objectives•1 minute
- Common Definitions•2 minutes
- Overview•1 minute
- Why AI is needed in Healthcare•5 minutes
- Examples of AI in Healthcare•8 minutes
- Growth of AI in Healthcare•3 minutes
- Questions Answered by AI•2 minutes
- AI Output•4 minutes
- Think beyond area under the curve•1 minute
- Recap•2 minutes
2 readings
- Study Guide Module 1•0 minutes
- Citations and Additional Readings•0 minutes
3 assignments•Total 40 minutes
- Reflection Exercise 1•10 minutes
- Reflection Exercise 2•10 minutes
- Knowledge Check•20 minutes
What's included
15 videos2 readings4 assignments
15 videos•Total 41 minutes
- Learning Objectives•1 minute
- Recap: Framework•1 minute
- Stakeholders•2 minutes
- Clinical Utility•2 minutes
- Outcome: Action Pairing, An Overview•4 minutes
- Lead Time•1 minute
- Type of Action•4 minutes
- OAP Examples•4 minutes
- Number Needed to Treat•3 minutes
- Net Benefits•3 minutes
- Decision Curves•4 minutes
- Feasibility overview•5 minutes
- Implementation Costs•2 minutes
- Clinical Evaluation and Uptake•5 minutes
- Summary•2 minutes
2 readings•Total 5 minutes
- Study Guide Module 2•5 minutes
- Citations and Additional Readings•0 minutes
4 assignments•Total 60 minutes
- Reflection Exercise 1•10 minutes
- Reflection Exercise 2•10 minutes
- Reflection Exercise 3•10 minutes
- Knowledge Check•30 minutes
What's included
19 videos2 readings5 assignments
19 videos•Total 47 minutes
- Learning Objectives•2 minutes
- The Problem•2 minutes
- Practical Questions Prior to Deployment•4 minutes
- Deployment Pathway•2 minutes
- Design and Development•3 minutes
- Stakeholder Involvement•2 minutes
- Data Type and Sources•3 minutes
- Settings•3 minutes
- In Silico Evaluation•2 minutes
- Net Utility & Work Capacity•2 minutes
- Statistical Validity•1 minute
- Care Integration, Silent Mode•3 minutes
- Clinical Integration, Considerations•3 minutes
- Technical Integration•1 minute
- Deployment Modalities•3 minutes
- Continuous Monitoring and Maintenance•2 minutes
- Challenges of Deployment•5 minutes
- Sepsis Example•2 minutes
- Summary•2 minutes
2 readings•Total 5 minutes
- Study Guide Module 3•5 minutes
- Citations and Additional Readings•0 minutes
5 assignments•Total 70 minutes
- Reflection Exercise 1•10 minutes
- Reflection Exercise 2•10 minutes
- Reflection Exercise 3•10 minutes
- Reflection Exercise 4•10 minutes
- Knowledge Check•30 minutes
What's included
18 videos2 readings5 assignments
18 videos•Total 41 minutes
- Learning Objectives•3 minutes
- Real World Examples of AI Bias•5 minutes
- Introduction - Types of Bias•1 minute
- Historical Bias•2 minutes
- Representation Bias•2 minutes
- Measurement Bias•2 minutes
- Aggregation Bias•2 minutes
- Evaluation Bias•2 minutes
- Deployment Bias•1 minute
- What is algorithmic Fairness•2 minutes
- Anti-classification•2 minutes
- Parity Classification•2 minutes
- Calibration•3 minutes
- Applying Fairness Measures•3 minutes
- Lack of Transparency•2 minutes
- Minimal Reporting Standards•3 minutes
- Opportunities and Challenges•3 minutes
- Summary•3 minutes
2 readings•Total 5 minutes
- Study Guide Module 4•5 minutes
- Citations and Additional Readings•0 minutes
5 assignments•Total 70 minutes
- Reflection Exercise 1•10 minutes
- Reflection Exercise 2•10 minutes
- Reflection Exercise 3•10 minutes
- Reflection Exercise 4•10 minutes
- Knowledge Check•30 minutes
What's included
18 videos2 readings4 assignments
18 videos•Total 53 minutes
- Learning Objectives•1 minute
- The Problem•3 minutes
- International Definitions Used for Regulatory Purposes•2 minutes
- Definition Statement & Risk Framework•6 minutes
- Valid Clinical Association•3 minutes
- Analytical Evaluation •1 minute
- Clinical Evaluation•3 minutes
- General Control•2 minutes
- de novo Notifications•2 minutes
- Software Modification•3 minutes
- TPLC•4 minutes
- Locked vs Adapted AI solutions•2 minutes
- Examples•4 minutes
- Non-Regulated Products•2 minutes
- EU Regulations•3 minutes
- Chinese Guidelines•2 minutes
- OMB Guidelines•6 minutes
- Summary•4 minutes
2 readings•Total 5 minutes
- Study Guide Module 5•5 minutes
- Citations and Additional Readings•0 minutes
4 assignments•Total 60 minutes
- Reflection Exercise 1•10 minutes
- Reflection Exercise 2•10 minutes
- Reflection Exercise 3•10 minutes
- Knowledge Check•30 minutes
Readings related to best ethical practices for AI in health care
What's included
3 readings
3 readings•Total 30 minutes
- Problem Formulation•10 minutes
- Identifying Conflicts of Interest•10 minutes
- Mitigating Conflicts of Interest•10 minutes
What's included
9 videos
9 videos•Total 42 minutes
- Introduction: Navigating the Intersections of AI and Medicine•3 minutes
- Life Cycle of AI•9 minutes
- A Deep Dive into Historical and Societal Dimensions•2 minutes
- Race-Based Medicine and Race-Aware Approach•5 minutes
- Bias Mitigation Strategies•5 minutes
- Exploring Potentials and Ethical Quandaries•5 minutes
- Dismantling Race-Based Medicine•4 minutes
- Deploying AI into Healthcare Settings•7 minutes
- Conclusion•1 minute
What's included
3 readings1 assignment
3 readings•Total 25 minutes
- Final Assessment Note•5 minutes
- Claim CME Credit•10 minutes
- Full Study Guide•10 minutes
1 assignment•Total 60 minutes
- Final Exam•60 minutes
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Reviewed on Dec 7, 2020
I was expecting the Medical genetics professor as a teacher also.
Reviewed on Dec 11, 2024
V easy to follow. Could finish at my own pace. Always theory went hand in hand with real life examples which made it interesting.
Reviewed on Dec 2, 2020
More examples would have been better to understand some of the concepts.
Frequently asked questions
Dates and Duration
Original Release Date: 08/10/2023
Expiration Date: 08/10/2026
Estimated Time to Complete: 9 hours and 30 minutes
CME Credits Offered: 9.50
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 9.50 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.
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. 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.
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.
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