Applying AI and ML in the Current Pandemic World
summary
Uses graph neural networks to predict infection links and produce individual and zonal risk scores for targeted interventions, and runs a bio‑carrier simulation to prioritize which small subset to vaccinate for herd effect. Combines LSTM with a GAN‑based impact model that outputs a demand offset to correct conventional time‑series forecasts, and a predictive‑maintenance pipeline for ventilators. Demo ties IBM Cloud data and Watson: demand forecasting, route optimization, cold‑chain monitoring and a workforce optimizer that handles 240 employee hours per site.
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chapters (5)
- 0:00Introduction to AI in pandemic
- 3:12Contact tracing with graph networks
- 6:23Medical supply demand forecasting
- 14:10Vaccine distribution challenges
- 18:25Workforce optimization demo
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