How Aether Harmonizes Data Across Labs, Imaging Centers, and Hospitals

The silent problem underneath every health app

On the surface, health apps look simple. Upload reports, see trends, share with doctors. Underneath, the reality is messy. Every lab, imaging center, and hospital uses slightly different names, units, and layouts for the same ideas.

If you ignore this, any health graph or AI system you build will be fragile. Harmonization is the quiet work that makes everything else possible.

The real world chaos of medical data

On paper, healthcare has standards. In practice:

• One lab calls a test HbA1c, another calls it Glycosylated Hemoglobin.
• One reports in percent, another in mmol per mol.
• Reference ranges change with machine, method, and population.
• PDFs come in every possible layout, font, and orientation.

Imaging reports add their own variety, with mixed narratives and templates. Hospitals use their own discharge formats and codes. For a human doctor, experience makes this manageable, if painful. For software, every variation is a potential failure.

Why harmonization matters for health graphs

A health graph is only as good as its structure. Patients want:

• Lab trends over years, regardless of where they tested.
• Imaging findings connected with labs, medications, and events.
• AI models that see real patterns, not template quirks.

This requires the system to understand that HbA1c from Lab A and Glycosylated Hemoglobin from Lab B are the same parameter, that creatinine values in different units are comparable after conversion, and that a CT chest and CT thorax may be similar events.

Without harmonization, you do not get one health graph. You get many fragments that never really connect.

How Aether harmonizes lab data

Aether treats every incoming report as raw material, not as clean data. The pipeline for labs includes:

• Parsing digital exports and scanned PDFs using vision and language models.
• Normalizing local test names to a consistent internal vocabulary.
• Aligning with standards like LOINC where possible, while preserving original labels for traceability.
• Detecting units and converting to canonical units when appropriate.
• Saving original units and reference ranges to maintain a safe audit trail.
• Anchoring every value on a correct timeline with date, and where available, time.

• LOINC codes for lab and clinical observations
• HL7 FHIR resources for laboratory data

Harmonizing imaging and hospital data

Labs are only one part of the story. Imaging and hospital records have their own structure and language. For imaging, Aether:

• Identifies modality and body region, such as CT chest or MRI brain.
• Extracts key findings and impressions from narrative reports.
• Maps common terms to a consistent internal vocabulary.

For hospital data, Aether:

• Marks important events such as admissions, surgeries, ICU stays, and discharges.
• Captures diagnoses, procedures, and discharge plans.
• Links diagnoses to standard codes like ICD where possible, without depending on them being present in every document.

Once harmonized, a timeline can show an abnormal troponin value, a coronary procedure, and medication changes as one story instead of three separate PDFs.

Why this matters for AI and for humans

Harmonization sounds technical, but the benefits are very human.

• Doctors see trustworthy trends and consistent dashboards, no matter where tests were done.
• Patients see one continuous journey, not a pile of disconnected files.
• AI models learn patterns that are more likely to be real and not artifacts of layout or naming.

Without harmonization, you end up building advanced features on top of sand.

Aether's philosophy in one line

Aether's philosophy is simple: do the hard normalization work once, so doctors and patients never have to think about it. The reward is a health graph that feels natural and consistent, no matter where the underlying data came from.

Sources and further reading

• HL7 FHIR standards for health data exchange
• LOINC coding system for lab and clinical observations
• Integrating the Healthcare Enterprise profiles for interoperability

Information only. Not implementation guidance. Real world integrations must follow local policy, contracts, and regulation.

Next steps

• If you run a lab or imaging center, document your current formats and units.
• If you are a hospital, map which systems hold which parts of the record.
• Talk to Aether about how your existing data can be harmonized into a single health graph.