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Phase 2 · Week 3
⏱ 14 minutes
Lesson 3.1
Lesson 3.1

Example Gallery: Healthcare Agents

Lesson Overview
Watch: Agentic AI use cases in healthcare — real clinical applications (20 min)

How to Use This Gallery

For each example: understand the pattern, then ask yourself the activation question. The gallery is a tool for developing project instinct, not a reading exercise.

Read what the agent does. Identify who it helps and why it matters. Note what it needs to work. Answer the activation question.

Healthcare Examples

Slide 1
01
Medication Reminder and Missed-Dose Alert
What it does:

Monitors a patient's medication schedule, sends reminders via SMS, and alerts a caregiver if a dose is missed for more than two hours.

Who it helps:

Elderly patients managing multiple medications. Their families who cannot be present for every dose.

Why it matters:

Missed doses cause thousands of preventable hospital readmissions every year. A consistent reminder system costs pennies per day.

What it needs:

A messaging API (Twilio), a simple schedule database, a PDF reader for prescription documents.

02
Discharge Letter Decoder
What it does:

Reads a hospital discharge letter, extracts key action items, and presents them as a plain-language checklist the patient can actually follow.

Who it helps:

Patients and families navigating post-hospital care. Discharge letters are written for clinicians, not patients.

Why it matters:

Failure to follow discharge instructions is a leading cause of 30-day readmission. Most patients do not understand their own letters.

What it needs:

A PDF/document parser, a language model for summarisation, a basic interface for output delivery.

03
School Flu Sentinel
What it does:

Monitors public flu incidence data and automatically sends a bulletin to school administrators when regional thresholds are crossed.

Who it helps:

School health coordinators, parents, and public health teams who currently check data manually and inconsistently.

Why it matters:

Early warning gives schools time to implement preventive measures before an outbreak becomes a closure.

What it needs:

A public health data API, email or messaging integration, simple threshold logic.

04
Mental Health Check-In Agent
What it does:

Sends daily check-in questions about mood and sleep, tracks trends over time, and shares a weekly summary with a counsellor if patterns suggest distress.

Who it helps:

Students and young adults who would not proactively seek support.

Why it matters:

Early detection of mental health decline dramatically improves outcomes.

What it needs:

A conversational interface, a mood-tracking database, strict privacy controls and explicit consent mechanisms.

Slide 2
Slide 3
Slide 4
Watch: AI in healthcare — from concept to clinical reality (8 min)
✏️ Student Reflection
Which of these four examples connects most directly to a problem you have personally encountered or witnessed? Describe what you would change or extend to make it more useful for your specific context. Write 3–5 sentences.

📝 Your Lesson Submission

Share your reflection, ask a question, or leave a comment. The bioERGOtech team will respond.

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