Data Science x Public Health

Est. audience

100

Apple rating

5 from 3

Cadence

Daily

Latest

2026-05-13

By

BJANALYTICS

Based on

12 recent episodes

• Covers: Statistical modeling limitations, epidemiology techniques, survival analysis, and data science challenges in public health systems.
• For: Data scientists, epidemiologists, biostatisticians, and public health researchers.
• Best for: Technical professionals applying data science and statistical modeling to public health challenges.
• Skip if: General consumers or business professionals outside health data and epidemiology.

Start with

• In Theory, Model Averaging Works. In Reality… It Doesn’t: Explains why model averaging overpromises when combined models share identical blind spots.
• This Is Why Resource Allocation Models Don’t Work (And Nobody Talks About It): Breaks down why optimization models fail when applied to rigid health system constraints.
• Everyone Uses AI Triage Tools… But They Fail When the Health System Is the Real Problem: Discusses why predictive AI triage models fail when operational bottlenecks are ignored.

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Summarised by AI from 12 recent episodes. Audience estimate and Apple rating from Podscan, checked 2026-11-03; treat the estimate as a guide and ask the show for its own numbers. Prices are not included. Report a mistake.