AI in the Real World Section 102

AI in Healthcare

What changes when the model's output touches a patient — messy hospital data, rare events, and mistakes that hurt real people.

8 of 8 lessons published Three reading levels on every lesson

Start with “What hospital data actually looks like”

Lessons in order

Work top to bottom. Each lesson assumes the one above it.

  1. What hospital data actually looks like
  2. Irregular clinical time series
  3. Predicting patient deterioration
  4. Label leakage in clinical models
  5. Survival analysis and censored outcomes
  6. False alarms and alert fatigue
  7. Validating a model before it touches patients
  8. When medical AI has caused harm