Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
Evaluations of AI Applications in Healthcare is a beginner-level online programme offered by the Stanford University School of Medicine which is accredited by the Accreditation Council for Continuing Medical Education (ACCME). Evaluations of AI Applications in Healthcare Certification Syllabus, prepared by Tina Hernandez-Boussard and Mildred Cho, will provide the candidates with a deep understanding of the application of artificial intelligence in healthcare and evaluation of the effects of AI healthcare solutions.
Offered by Coursera, the Evaluations of AI Applications in Healthcare Certification Course is provided completely in the mode with a flexible deadline where the students can set the deadline as per their own schedule. Evaluations of AI Applications in Healthcare Certification by Coursera is the fourth in the five courses of AI in Healthcare Specialization.
The Highlights
- Provided by Coursera
- Approximately 11 hours of programme
- Offered by the Stanford University
- Flexible Deadlines
- Self-Paced Learning Option
- Shareable Certificate
- Beginner Level Course
- Financial Aid Available
- 100% Online Course
Programme Offerings
- English videos with multiple subtitles
- practice quizzes
- Graded Assignments with peer feedback
- graded Quizzes with feedback
- Graded Programming Assignments
- Course Videos & Readings
- EMI payment options
- 14 day refund period.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
Evaluations of AI Applications in Healthcare Certification Fee is tabulated below:
Description | Total Fee in INR |
Course Fee, 1 month | Rs. 6,638 |
Course Fee, 3 months | Rs. 13,276 |
Course Fee, 6 months | Rs. 19,915 |
Eligibility Criteria
Certification Qualifying Details
To get hold of the Evaluations of AI Applications in Healthcare Certification, the students are required to successfully finish all the proceedings of the programme such as course materials, lecture videos, quizzes, assignments, etc.
What you will learn
After the Evaluations of AI Applications in Healthcare Training, the students will be able to make a detailed understanding of
- Best practices of AI applications in healthcare.
- Standard evaluation metrics
- Challenges of regulation of AI applications
- Integration of AI into clinical workflows
- Evaluations of AI in Healthcare
- AI Deployment
Who it is for
Evaluations of AI Applications in Healthcare Classes is a better opportunity for the following professionals:
- Doctor
- Health Inspector
- Health Officer
- Nurse
- Medical Lab Technician
Admission Details
Step1- At first, the students will have to register and sign up on https://www.coursera.org/ to get access to the courses offered by Coursera.
Step 2 - After activating the Coursera account, the candidate can sign in.
Step 3 - Then, the candidate can search the ‘Stanford University’ in the search column, and then, the courses offered by Stanford University will appear on the screen.
Step 4 - Then, find the course ‘Evaluations of AI Applications in Healthcare’ in the list and click on it.
Step 5- Then, the page of the course will appear on the screen, and then, click on the option ‘enroll’. The students can enroll in the programme either free of cost or pay the fee prescribed by Coursera.
The Syllabus
Videos
- Learning Objectives
- Common Definitions
- Overview
- Why AI is needed in Healthcare
- Examples of AI in Healthcare
- Growth of AI in Healthcare
- Questions Answered by AI
- AI Output
- Think beyond area under the curve
- Recap
Readings
- Study Guide Module 1
- Citations and Additional Readings
quizzes
- Reflection Exercise 1
- Reflection Exercise 2
- Knowledge Check
Videos
- Learning Objectives
- Recap: Framework
- Stakeholders
- Clinical Utility
- Outcome: Action Pairing, An Overview
- Lead Time
- Type of Action
- OAP Examples
- Number Needed to Treat
- Net Benefits
- Decision Curves
- Feasibility overview
- Implementation Costs
- Clinical Evaluation and Uptake
- Summary
Readings
- Study Guide Module
- Citations and Additional Readings
quizzes
- Reflection Exercise 1
- Reflection Exercise 2
- Reflection Exercise 3
- Knowledge Check
Videos
- Learning Objectives
- The Problem
- Practical Questions Prior to Deployment
- Deployment Pathway
- Design and Development
- Stakeholder Involvement
- Data Type and Sources
- Settings
- In Silico Evaluation
- Net Utility & Work Capacity
- Statistical Validity
- Care Integration, Silent Mode
- Clinical Integration, Considerations
- Technical Integration
- Deployment Modalities
- Continuous Monitoring and Maintenance
- Challenges of Deployment
- Sepsis Example
- Summary
Readings
- Study Guide Module
- Citations and Additional Readings
quizzes
- Reflection Exercise 1
- Reflection Exercise 2
- Reflection Exercise 3
- Reflection Exercise 4
- Knowledge Check
Videos
- Learning Objectives
- Real World Examples of AI Bias
- Introduction - Types of Bias
- Historical Bias
- Representation Bias
- Measurement Bias
- Aggregation Bias
- Evaluation Bias
- Deployment Bias
- What is algorithmic Fairness
- Anti-classification
- Parity Classification
- Calibration
- Applying Fairness Measures
- Lack of Transparency
- Minimal Reporting Standards
- Opportunities and Challenges
- Summary
Readings
- Study Guide Module
- Citations and Additional Readings
quizzes
- Reflection Exercise 1
- Reflection Exercise 2
- Reflection Exercise 3
- Reflection Exercise 4
- Knowledge Check
Videos
- Learning Objectives
- The Problem
- International Definitions Used for Regulatory Purposes
- Definition Statement & Risk Framework
- Valid Clinical Association
- Analytical Evaluation
- Clinical Evaluation
- General Control
- de novo Notifications
- Software Modification
- TPLC
- Locked vs Adapted AI solutions
- Examples
- Non-Regulated Products
- EU Regulations
- Chinese Guidelines
- OMB Guidelines
- Summary
Readings
- Study Guide Module
- Citations and Additional Readings
quizzes
- Reflection Exercise 1
- Reflection Exercise 2
- Reflection Exercise 3
- Knowledge Check
Readings
- Problem Formulation
- Identifying Conflicts of Interest
- Mitigating Conflicts of Interest
Readings
- Final Assessment Note
- Claim CME Credit
- Full Study Guide
quizzes
- Final Exam
Instructors
Stanford Frequently Asked Questions (FAQ's)
The course is provided in 100% online mode.
The programme can be completed within about 11 hours.
The course is administered by Stanford University School of Medicine which is accredited by the Accreditation Council for Continuing Medical Education (ACCME).
Yes, the instalment mode is available for the fee payment.
No, Coursera does not provide placement support for the students.