Grab Lab Results from Any Health Checkup App Screenshot — Compare Year Over Year
Manually retyping lab results from two years of health app screenshots into a comparison spreadsheet takes 3 minutes per report — this aligns them in 5 seconds.
5s per screenshot · Up to 99% accuracy on printable text
What You Can Pull from a Health Checkup App Screenshot
Labcorp, Quest, 美年大健康, 爱康国宾 — every provider displays results as a table, but the column order, labeling, and units differ. With Custom Column Extraction, you type the fields you need and the AI reads them by meaning, not position.
The biomarker name — "Glucose, Serum", 葡萄糖, 甘油三酯. Read regardless of position.
The numeric measurement — 102 mg/dL, 5.7%. Handles flagged values like "185 H" where the flag is merged.
The lab's normal range — "65-99 mg/dL" or "70-100 mg/dL". Captured as a separate field for cross-lab comparison.
mg/dL, mmol/L, %, ng/mL — the unit text that traditional OCR skips. Preserved as a distinct field.
Out-of-range indicators — "H" for high, "L" for low. Extracted as a separate column.
Two Years of Lab Results — Same Tests, Different Layouts
Why Year-over-Year Comparison Is Painful
Every lab app uses a different column order. Quest, Labcorp, and 美年大健康 all arrange Test, Result, Reference Range, and Flag differently. Manual comparison means reordering columns by eye.
Reference ranges differ between labs for the same test. Labcorp's glucose range is 65-99 mg/dL; Quest's is 70-100 mg/dL. A result of 98 is "normal" at Quest but flagged at Labcorp. As one Reddit user noted, "nothing worse than having to reformat everything because one lab uses mg/dL and another uses mmol/L."
No app lets you export two years as a spreadsheet. Health portals show results one year at a time with no CSV export. Screenshots are the only portable option — but traditional OCR cannot align two different layouts into a single table.
How Semantic Extraction Aligns Any Layout
Name the fields — AI reads them by meaning, not position. Define "Test Name, Result, Reference Range, Unit." Whether Reference Range appears left of Result (Labcorp) or right (Quest), the AI locates it by semantic role.
Batch years together — same column set. Upload last year's Quest screenshot and this year's Labcorp screenshot into the same batch. The same five columns apply to both. The output is one unified spreadsheet.
Reference range is captured as its own field. Traditional OCR merges "65-99 mg/dL" into the result cell or drops it. Keeping Reference Range separate retains the lab-specific context for accurate comparison.
From Two Years of Screenshots to One Comparison Spreadsheet
Screenshot Both Years' Reports
Open last year's results in your health app — MyQuest, Labcorp, or 美年大健康 — and take a screenshot. Do the same for this year's. Each captures the full test table: names, values, ranges, units, and flags. The layout may differ between years — that is expected. Drag both into a single upload.
Name the Fields Once
Type the column names: Test Name, Result, Reference Range, Unit, Flag. The AI reads each screenshot independently — on a Quest screenshot it locates glucose by its label, captures the reference range, and notes any flag. On a 美年大健康 screenshot it does the same, even though the layout is in Chinese and columns appear in a different order.
Download a Side-by-Side Comparison
Processing takes about 5 seconds per screenshot. The output is one XLSX file with rows from both years aligned under the same column headers. Row 1: last year's glucose from Quest — 102 mg/dL, range 70-100. Row 2: this year's glucose from Labcorp — 98 mg/dL, range 65-99. Roughly 36x faster than manual typing (~3 min per report vs ~5s).
When It Works Best — and When to Be Cautious
Knowing these boundaries helps you get consistent results when comparing lab values across years and providers.
When It Works Best
Clear, full-resolution screenshots of health app tables. Machine-rendered lab values achieve up to 99% accuracy.
Mixed providers in a single batch. Upload screenshots from Quest, Labcorp, and 美年大健康. The AI outputs one spreadsheet with consistent headers.
Year-over-year comparison with reference range context. Reference Range is captured as a separate field, making results from different labs comparable.
When to Be Cautious
Heavily compressed or forwarded screenshots. A screenshot of a screenshot loses resolution on small reference range text. Use the original when possible.
Scrolling screenshots that truncate the table. If the app requires scrolling, take multiple screenshots to cover the full list, or use the PDF export if available.
Visible data only — no clinical interpretation. The tool extracts what the app displays. It does not interpret medical significance. Share the spreadsheet with your healthcare provider for review.
Frequently Asked Questions
Can I compare results from Labcorp and Quest in the same spreadsheet?
Yes. Define columns like Test Name, Result, Reference Range, and Unit. Quest and Labcorp use different column orders, but the AI reads values by meaning. A glucose value of 102 mg/dL from Quest and 99 mg/dL from Labcorp both land in the Result column.
Can I batch last year's and this year's screenshots together?
Yes. Upload last year's MyQuest screenshot and this year's Labcorp screenshot into the same batch. Define columns once — Test Name, Result, Reference Range, Unit, Flag. The output is one spreadsheet with both years side by side.
What if the reference range is different between this year and last year?
The Reference Range column captures the exact range printed on each screenshot. If last year's Quest says "70-100 mg/dL" for glucose and this year's Labcorp says "65-99 mg/dL," both are preserved. A result of 98 is normal at Quest but flagged by Labcorp's standard.
Does the AI handle Chinese test names from 美年大健康 or 爱康国宾?
Yes. The AI reads both Chinese (葡萄糖, 甘油三酯) and English (Glucose, Triglyceride) test names. Define Test Name and it captures the name in the screenshot's language.
How accurate is extraction for lab values from a health app screenshot?
For clear screenshots of Labcorp and Quest portals, accuracy on numerical values reaches up to 99%. Compressed screenshots reduce accuracy. The tool extracts visible text only; it does not interpret clinical meaning.
Deep dives into health screenshot extraction: Batch processing health app screenshots including checkup reports into a single structured spreadsheet · General guide to extracting data from screenshots including lab results and health summaries
Return to the health & fitness app overview — see all supported apps and their extraction capabilities.