Filling the Gaps: How Bayesian Networks Learn to Guess Smarter in Intensive Care
Opening — Why this matters now Hospitals collect oceans of data, but critical care remains an island of uncertainty. In intensive care units (ICUs), patients’ vital signs change minute by minute, sensors fail, nurses skip readings, and yet clinical AI models are expected to predict life-or-death outcomes with eerie precision. The problem isn’t data scarcity — it’s missingness. When 30% of oxygen or pressure readings vanish, most machine learning systems either pretend nothing happened or fill in the blanks with statistical guesswork. That’s not science; that’s wishful thinking. ...