HomeBench v0 · compiled from the post-op fall-prevention guideline (customer #1: HomeReady)

The flight simulator for home-health AI.

HealthDojo turns real clinical guidelines into synthetic homes with exact, verified labels, so AI companies can pressure-test their models before a single patient trial. Guidelines in, benchmarks out.

The report card, at a glance

The problem

Patients go home on a walker. The house decides whether they fall.

1 in 3

joint-replacement patients fall within a year of surgery.

~31%

of falls are caused by the environment: rugs, missing grab bars, low toilets.

26% / 38%

fewer falls with home modification, 38% in high-risk patients (Cochrane 2023).

Home-health AI is shipping vision models into homes. Nobody can test them: real homes have no ground truth. HealthDojo compiles one from the guideline.
01 · guideline

Guideline

Start from the post-op fall-prevention guideline (CDC STEADI, HOME FAST, SAFER-HOME).

02 · rubric

Rubric

Draft hazard checklist, pending clinician review. Every row cites a guideline line.

03 · scenes

Scenes

Label before pixels: seed one hazard, render, verify it's really there. Boxes come free.

04 · report card

Report card

Any home-health model runs the same eval out of the box: hits, misses, false alarms.

HomeBench leaderboard

Who can see a dangerous home?

Every model sees the same scenes and the same 35-hazard checklist. Click a column to sort.

Score = mean of recall and (1 − false-alarm rate). Recall = seeded hazards found. False alarm = model reports a hazard we verified is not in the room (e.g. "no grab bar" when there are three). Precision = hits ÷ (hits + verified false alarms). Loc IoU = box overlap on hits.
Where every model fails

Hardest hazards · mean recall across models

Recall by hazard type

Recall by room

0% found
100% foundn/a: not tested yet
Object = something in the way (rug, cord, clutter). Absence = something missing (grab bar, stair rail). Measurement = geometry (toilet height, doorway too narrow for a walker). Lighting = too dark to see the path.
Scene explorer

Open any room. See what each model saw.

Each tile is a verified scene. The bar shows how many models found its hazard. Click to compare the clean room with the hazard edit and overlay any model's boxes.

Next

Walk the home in 3D

From single photos to walkable worlds: the same seeded hazards, explored the way a patient moves through a house.