AI in Healthcare
Diagnose. Predict. Heal.
Course Objective
To introduce learners to the powerful role AI plays in modern healthcare — from diagnosing diseases to predicting risks and assisting doctors in improving patient outcomes — while also exploring its ethical and human impact.
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Module 1: Introduction to AI in Healthcare
- What is AI? (Quick recap for new learners)
- Overview of healthcare challenges AI helps solve
- Examples: From fitness trackers to AI in hospitals
- Video: “How AI Helped a Doctor Save a Life”
Module 2: Diagnosis with AI
- How AI detects diseases from scans and images
- AI in X-rays, MRIs, and pathology
- Case study: Google’s AI for eye diseases
- Interactive: Label a “fake” vs. “AI-analyzed” medical image
Module 3: Predicting Health Risks
- Using AI to predict diseases before symptoms appear
- AI in monitoring chronic illnesses (diabetes, heart)
- Real-world examples: IBM Watson, Apple Health
- Create a simple risk-prediction questionnaire using AI logic
Module 4: Virtual Doctors & Chatbots
- What are medical chatbots?
- How patients get advice using AI-powered apps
- Demo: Use a free health AI chatbot (like Babylon or Ada)
- Build a basic chatbot using a no-code tool
Module 5: AI in Wearable Devices
- Smartwatches and fitness bands: How they use AI
- Heart rate, sleep, stress tracking
- Data collected and how it’s used by doctors
- Project: Track your daily health and analyze patterns
Module 6: Hospitals of the Future
- Smart hospitals with AI-based systems
- Robot nurses, automated check-in, digital diagnosis
- Benefits: Faster care, better safety, lower costs
- Draw/design your idea of a “Hospital of the Future”
Module 7: Ethics & Challenges
- Can we trust AI with life and death decisions?
- Data privacy in health tech
- Human doctors vs AI tools – What’s better?
- Debate: Should robots be allowed to perform surgery?
Module 8: Mini Project (Choose One)
- Design a virtual health assistant interface
- Create a simple AI health log (mood, sleep, symptoms)
- Make a poster: “How AI is Changing Hospitals”
Learning Activities
- Short quizzes after each module
- Watch short interviews with doctors using AI
- Explore real tools like Google Fit, Ada, HealthifyMe
- Brainstorm AI solutions for rural health issues
Course Outcome
By the end of this course, learners will:
- Understand how AI is improving medical diagnosis and care
- Be able to explain how AI predicts health risks
- Explore real-life tools and future possibilities
- Reflect on the human side of AI in healthcare
Duration:
- 1–2 weeks (8 modules + project)
- Level: Beginner
- Format: Online / Classroom / Blended
- Tools Used: ChatGPT, Canva, Ada Health, Google Fit, Scratch or Glide (for chatbot)