- Artificial Intelligence and Machine Learning (AI/ML)
- Healthcare Industry Knowledge
- Patient Communication
- Diagnostic Tests
- Health Disparities
- Health Policy
- Clinical Assessment
- Responsible AI
- Healthcare Ethics
- Clinical Research
- Probability & Statistics
- Health Informatics
Data Augmented Technology Assisted Medical Decision Making
Completed by Patricia Corbin
September 15, 2024
11 hours (approximately)
Patricia Corbin's account is verified. Coursera certifies their successful completion of Data Augmented Technology Assisted Medical Decision Making
What you will learn
Describe the crucial role, strengths, limitations of AI and ML in evidence-based medical decision making
Evaluate machine learning studies for bias and systematic error to enhance diagnostic decisions.
Apply the results of machine learning studies and outputs to diagnostic decisions.
Identify legal and ethical issues and best practices for AI and ML use in healthcare settings
Skills you will gain
