Biomarker relationships

Overview of our functionalities for doing a contextual interpretation of your lab values.

We a) narrow down lab value reference ranges for the individual. Based on this we can do a b) anomaly detection. c) Group and compare lab values with different symptomologies associated. d) Predict additional lab values based on a subset of mesurements to simulate changes.

a) and b)

First we will prepare your personal data so it can be processed by our model.

1. Input of your lab values.
2. Generation of a personal rest value
3. New reference ranges drawn

1. Lab values

Your sample is compared with thousands of other samples in our database. Samples that are contextually most similar are identified.

2. Personal rest value

Your personal anchor point or Le Chatelier equlibrium based on the analysis. This is used as your digital signature for comparing to other samples.

3. Anomaly detection

New reference ranges are drawn based on the distance from the personal rest value. Identify values that contextually differ from the reference data.

c)

4. Use personal rest value as base for comparison
5. Identify ideal target rest value based on symptomologies

4. Culturally encoded snapshot

With a uniform language your lab values can be compared to thousands of other samples.

5. Target

A spectrum of risk analysis can be performed and identifying subgroups that most closely reflect the individual. A least effort target is generated that is associated with the lowest risk for symptomologies.

d)

6. Input a subset of values
7. Predict other values based on the samples fuond in the database.

6. Subset of biomarkers

Incomplete sets of biomarkers can be completed by finding contextually most relevant samples in the database and compiling a callage set.

7. Predicted values

Create a synthetic blood sample based on the subset of biomarkers. This is used for simulating changes in individuals and planning possible interventions.