AI for cholesterol & lipid analysis

One lipid panel is a snapshot. Your trend, in context, is the actual signal.

What we’re actually working with

Lipid panels (total, LDL, HDL, triglycerides, ApoB, Lp(a)) are the most-tracked cardiovascular data most adults will ever own.

Why doing this without a method fails

Most people see a single number and react. Few read their own trend across years, diet shifts, or medication changes.

How the method handles cholesterol

Layer 01

Research

Use sourced AI to read the actual evidence on ApoB vs LDL-C, Lp(a) interpretation, and lifestyle effect sizes.

Layer 02

Ledger

Build a multi-year lipid ledger annotated with diet, training, weight, and medication.

Layer 03

Protocol

Test one intervention (e.g. saturated fat reduction, statin start) over 12 weeks with a clean before/after.

Three prompts you can use today

Paste any of these into the AI chat tool you already use. No setup.

Lipid trend

Here are 5 years of fasting lipid panels including ApoB. Show trends, flag any drift, and tell me what's meaningfully different from year 1.

Diet experiment

I changed my diet 12 weeks ago. Compare my pre and post lipid panel and tell me what changed beyond noise.

Cardio risk brief

Build a 1-page cardiovascular risk summary for my GP based on my lipids, BP, family history, and lifestyle.

Common questions

Should I focus on LDL or ApoB?+

The course covers the current evidence and where each is most useful.

Will AI tell me to start a statin?+

No. That's a clinician's call. AI helps you bring better data to that conversation.

Is Lp(a) worth testing?+

Once in a lifetime, for most adults. The course explains why.

Start with 10 free days.

The free 10-day email challenge teaches the same method on whatever data you already collect. No credit card.