LAH0022 - Transforming Healthcare with AI
Course Description
Explore how AI is transforming diagnostics, imaging, drug discovery, and patient care. You will gain hands-on experience and examine real-world case studies. Learn to navigate data challenges, ethics, and privacy concerns while designing innovative solutions. Discover emerging trends in personalized medicine, robotic surgery, and the future of healthcare technology.
This engaging course was designed for healthcare professionals, technologists, and students seeking careers in the medical field.
Course Outline
Week 1: AI Applications in Healthcare
Introduction to AI in Healthcare
• Overview of AI in healthcare
• Applications: diagnostics, personalized medicine, patient monitoring
• Activity: Identify potential AI applications in a healthcare scenario
Data in Healthcare
• Types of healthcare data: EHRs, imaging, and genomics
• Data challenges: interoperability, privacy, and quality
• Activity: Analyze a healthcare dataset for insights using Python or Excel
Week 2: AI in Diagnostics, Drug Discovery, and Genomics
AI in Diagnostics and Imaging
• AI for medical imaging: X-rays, CT scans, MRIs
• Predictive models in diagnostics
• Activity: Explore a pre-trained AI model for medical imaging (e.g., PyTorch or TensorFlow)
• AI for drug development and genomic analysis
• Case studies: AI in COVID-19 vaccine development
• Activity: Review a published AI-based drug discovery case study
Week 3: Patient Care and Ethical Considerations
AI in Patient Monitoring and Telemedicine
• Wearables and IoT in healthcare
• AI-powered telemedicine platforms
• Activity: Simulate patient data monitoring with AI tools
Ethical Challenges in Healthcare AI
• Bias in healthcare AI algorithms
• Privacy and security of patient data
• Activity: Debate on the ethical implications of using AI for genetic predictions
Emerging Trends in AI Healthcare
• AI in robotic surgery and virtual health assistants
• Trends: federated learning, personalized medicine
• Activity: Research and present an emerging AI trend in healthcare
Capstone Project
• Capstone: Design and present an AI solution for a healthcare problem (e.g., patient triage, resource optimization).
• Peer feedback and discussion on implementation challenges
Learner Outcomes
Notes
Due to construction in the computer lab, the 2nd week of this course will be held in an online live format.
7/28 & 7/30: In-person at Harper (Palatine)
8/4 & 8/6: Online live (Link will be shared by instructor)
8/11 & 8/13: in-person at Harper (Palatine)