🧪 Omnipotent Medical Omniscient Medical Simulation

A single omniscient sensor hub feeds six streams of clinical evidence into a naive-Bayes differential-diagnosis network. Toggle findings — chest pain, dyspnea, fever, tachycardia, hypoxia, diaphoresis — and watch the posterior probability of six candidate diagnoses (myocardial infarction, pulmonary embolism, pneumonia, panic attack, sepsis, and a low-acuity baseline) update in real time, exactly via Bayes' theorem under a conditional-independence assumption. The 3D holographic network renders every evidence node and diagnosis pylon as live geometry: evidence spheres glow when toggled on, and each diagnosis pylon's height and color intensity track its current posterior probability, with the leading diagnosis highlighted once it clears your chosen certainty threshold.