Lectures, tutorials, and explainers on AI, data, and health technology — built for practitioners, researchers, and curious minds.
Start with the fundamentals of machine learning applied to clinical problems.
4 modulesBuild KPI dashboards and interpret data for operational health decisions.
3 modulesFrom platform selection to patient onboarding in underserved settings.
3 modulesAdvanced methods: social network analysis, extreme value modelling, NLP.
5 modulesSentiment analysis, topic modelling, and word networks from health discussions.
3 modulesA plain-language walkthrough of how ML models are trained, validated, and deployed inside EHR systems to flag high-risk patients in real time.
Watch on YouTubePlain-language introduction to machine learning and how it supports diagnostics, triage, and care pathways — no coding required.
Read ArticleFrom KPIs to dashboards — how to turn raw patient data into clear, actionable intelligence for clinics and public health programs.
Read ArticleWhat to consider when launching remote care in underserved communities — infrastructure, training, and patient trust.
Read ArticleHow statistical methods for rare events can save lives by giving humanitarian organizations earlier warning of crises.
Read ArticleHow PulseVision AI maps the language of online health discussions — from raw Reddit text to an interactive force-directed graph.
Read ArticleA practical look at connecting patient wearables to central systems — what works, what fails, and how to avoid the common pitfalls.
Read Article