🧩 In medical ML models, as in causal inference, not all variables are equal:

Mediators transmit the effect.

Confounders bias the effect.


Mediators should be excluded, confounders should be utilized.

👉 Explore your health data: build no-code Web ML models:
🔗 mlhs.ink/Playground/#SDC

#MedAI #CausalInference #DigitalHealth #WebML

🧩The real cause of morbidity is often the interaction between exposures — whereas predictors alone are not necessarily harmful.

We know:
1️⃣ Cortisol/adrenaline stress → reduced life expectancy
2️⃣ Skydiving → cortisol/adrenaline surge
3️⃣ But… Skydiving ≠/? Life expectancy directly

👉 Only the combination of cortisol/adrenaline and exposure time drives the outcome — morbidity.

📖 For more on interactions, read this great paper by Tyler J. VanderWeele: Interaction Tutorial (PDF)

#CausalInference #MedAI #DigitalHealth