Generative AI in Healthcare: Transforming Medicine and Patient Care Training Course
Generative AI is a transformative technology that leverages machine learning models to generate new, synthetic instances of data, which can be used across a variety of healthcare applications.
This instructor-led, live training (delivered either online or on-site) is designed for healthcare professionals, data analysts, and policy makers at beginner to intermediate levels who wish to understand and apply generative AI within the healthcare context.
By the conclusion of this training, participants will be able to:
- Explain the core principles and practical applications of generative AI in healthcare.
- Identify opportunities where generative AI can enhance drug discovery and support personalised medicine.
- Apply generative AI techniques to medical imaging and diagnostic processes.
- Evaluate the ethical implications of deploying AI in clinical and medical settings.
- Develop effective strategies for integrating AI technologies into existing healthcare systems.
Course Format
- Interactive lectures and guided discussions.
- Abundant practical exercises and hands-on practice.
- Live implementation within a real-time lab environment.
Course Customisation Options
- To request a customised version of this training, please contact us to make arrangements.
Course Outline
Introduction to Generative AI
- Understanding the fundamentals of AI and machine learning
- Deep dive into generative models
- Exploring the landscape of generative AI in healthcare
Generative AI in Drug Discovery
- Accelerating drug design using AI
- Case studies: Success stories and key challenges
- Virtual screening and predictive modelling
Personalised Medicine through Generative AI
- Tailoring treatments with AI-driven insights
- Genomics and AI: A new era of personalisation
- Ethical considerations in AI-powered personalised medicine
Advancements in Medical Imaging
- Enhancing diagnostics with generative AI
- 3D medical imaging and AI-based reconstruction techniques
- Improving patient outcomes through AI-assisted imaging
Real-World Applications and Future Directions
- Integrating generative AI into clinical practice
- The future of AI in patient care and management
- Final project: Proposing an AI solution for a real healthcare challenge
Ethical and Societal Implications
- Navigating the ethical landscape of AI in healthcare
- Data privacy, security, and governance
- Preparing for the future: Policy and regulatory considerations
Summary and Next Steps
Requirements
- A basic understanding of machine learning concepts
- Familiarity with Python programming
- Introductory knowledge of biology and healthcare systems
Intended Audience
- Healthcare professionals
- Data analysts
- Policy makers
Open Training Courses require 5+ participants.
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Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
Adam - GE Aerospace Poland Sp. z o.o.
Course - Prompt Engineering for ChatGPT
Provisional Upcoming Courses (Require 5+ participants)
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