AI in Clinical Decision Support & Diagnostics
Overview
This Course Includes:
- On-demand videos
- Practice assessments
- Multiple hands-on learning activities
- Exposure to a real-world project
- 100% self-paced learning opportunities
- Certification of completion
This course empowers healthcare professionals to confidently integrate AI-driven clinical decision support systems (CDSS) into patient care. Learners explore how artificial intelligence is transforming diagnostics, risk prediction, and decision-making through innovations in medical imaging, predictive analytics, and bias detection. By engaging with real-world case studies and hands-on exercises, participants learn to apply AI tools and insights directly within clinical workflows to improve diagnostic accuracy, efficiency, and patient outcomes.
Participants also develop a deep understanding of the ethical and practical challenges surrounding AI in medicine, including algorithmic bias, transparency, and data privacy. Through interactive labs using free and open-access AI platforms, learners gain practical skills to interpret, validate, and implement AI recommendations responsibly. By the end of the course, they are equipped to lead the ethical and effective adoption of AI in healthcare—bridging human expertise with intelligent systems to deliver smarter, safer clinical decisions.
Skills You Will Gain
Learning Outcomes (At The End Of This Program, You Will Be Able To...)
- Define AI’s role and impact in clinical decision support.
- Evaluate AI-driven medical imaging and predictive analytics applications.
- Apply AI-generated insights to real-world patient diagnoses.
- Identify and address biases and ethical challenges in AI-assisted medicine.
Prerequisites
Basic understanding of clinical workflows and medical terminology; computer and internet access; interest in AI in healthcare.
Who Should Attend
Physicians, Radiologists, Nurses, Healthcare IT Specialists
