Health records · AI-assisted · non-diagnostic

Your lab results,
explained in plain language.

HealthTrack turns raw lab data into something you can actually read — with trends over time and grounded guidance that assists, but never diagnoses.

Result · HbA1c26 Apr 2026
Glycated hemoglobinAbnormal
6.5%▲ rising
reference 4.0–5.6% · independently sourced
Jan 2025 → Apr 2026 · six readings
What this means

Your HbA1c has risen steadily over the past year and is now above the normal range. It reflects average blood sugar over roughly three months, and is worth discussing with your doctor.

This is context, not a diagnosis. The trend and reference range are computed deterministically; the wording is drafted by an AI and reviewed before it reaches you.

Access control

Four roles, each sees exactly what it should

HealthTrack isn’t a single dashboard. It’s a permissioned system where every role has its own view and its own boundaries — enforced on the server, deny-by-default.

01
Patient

Owns their record. Sees results, trends, plain-language guidance, and reminders — and controls exactly what’s shared.

02
Caregiver

Sees only results a patient has explicitly shared. No trends, no advisor — access is scoped and revocable.

03
Lab

Uploads results, drafts summaries with AI, and extracts measurements from real lab PDFs with human review.

04
Admin

Operational only — approves labs, verifies licenses, views anonymized analytics. Never holds clinical data.

AI that assists

Intelligence where it helps — with a human in the loop

Result advisor

Explains what a result means and drafts follow-up reminders. Trends and flags are computed deterministically — the AI only writes the explanation, so it can’t invent a clinical value.

PDF extraction

Reads measurements from real lab reports (text layer or OCR), structures them against known analytes, and shows the lab exactly what it read — to correct before confirming.

Grounded guidance

Whole-picture guidance is drawn from your own results over a window you choose — never generic advice — and always framed as non-diagnostic.

Built with care

Safety is a design decision, not a disclaimer

Non-diagnostic by design

The system explains and contextualizes; it never diagnoses. Deterministic trend analysis is kept separate from AI-written text to eliminate hallucinated clinical values.

Sourced reference ranges

Flags are computed against independently-sourced clinical ranges — a lab can’t define its own “normal” and quietly flag away an abnormal result.

Separation of duties

Roles are strictly bounded and enforced server-side. An admin operates the system, but can never be assigned clinical results.

Synthetic data only

This is a portfolio build running entirely on synthetic records. No real patient data is involved.

Grounded in real sources

Explanations are backed by citations, not guesses

The advisor doesn't invent medical explanations. Every “what this means” is grounded in a curated knowledge base — 30 sourced passages from MedlinePlus, WHO, CDC, Mayo Clinic, Cleveland Clinic, and NORD, covering diabetes, cholesterol, hypertension, anemia, sickle cell disease, malaria, and typhoid.

Numeric flagging

Five core analytes — HbA1c, Total Cholesterol, LDL, HDL, and Triglycerides — are compared against reference ranges read directly from MedlinePlus and Johns Hopkins Medicine, one citation per number. Other numeric results are extracted and shown, but flagged “unknown” rather than guessed.

Coverage grows deliberately

Rapid, titer, and graded tests (malaria, typhoid, and others) are flagged against the assay's own reported cutoff or expected value — never a lab-invented range. New sourced ranges are added over time; accuracy comes before coverage.

MedlinePlusWHOCDCMayo ClinicCleveland ClinicNORDJohns Hopkins Medicine

See it for yourself

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