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Course Outline
Overview of Generative AI
- Grasping the fundamentals of AI and machine learning
- In-depth exploration of generative models
- The current state of generative AI in the healthcare industry
Application of Generative AI in Drug Discovery
- Speeding up drug design processes using AI
- Case studies: Analyzing successes and operational hurdles
- Virtual screening methods and predictive modeling
Personalized Medicine Enabled by Generative AI
- Customizing treatment plans with AI assistance
- Genomics and AI: Entering a new age of individualized care
- Addressing ethical issues in AI-driven personalized medicine
Progress in Medical Imaging
- Boosting diagnostic accuracy with generative AI
- 3D medical imaging and AI-based reconstruction methods
- Enhancing patient outcomes through AI-supported imaging
Practical Use Cases and Future Trajectories
- Incorporating generative AI into daily clinical workflows
- The prospective role of AI in patient management and care
- Capstone project: Designing an AI-based solution for a specific healthcare issue
Ethical and Social Consequences
- Navigating the ethical framework of AI in healthcare
- Managing data privacy, security, and governance
- Preparing for the future: Understanding policy and regulatory landscapes
Recap and Subsequent Actions
Requirements
- A foundational grasp of machine learning principles
- Proficiency in Python programming
- Basic knowledge of biology and healthcare system structures
Target Audience
- Clinical and non-clinical healthcare professionals
- Data analysts
- Policy makers
21 Hours
Testimonials (2)
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt
