Digital Health Twin
A digital health twin is a dynamic model of the body that updates as new medical data arrives. Unlike a static medical record, the twin reflects not only current diagnoses but also biomarker trends, risk factors, and predictions based on observation history.
From Medical Record to Living Model
Traditional medical documentation stores facts "at the time of visit": a 2022 diagnosis, last year's lab results, a post-surgery discharge summary. Clinicians must manually assemble the picture from scattered documents.
A digital health twin solves this differently:
- Aggregation — all documents from different clinics in one profile.
- Structuring — AI extracts biomarkers, diagnoses, prescriptions, and maps them to standard codes (LOINC, SNOMED CT).
- Dynamics — values tracked over time, not as isolated snapshots.
- Analytics — the system detects trends, deviations, and generates summary reports.
How Lissa Health Builds the Twin
Lissa Health implements the digital health twin through a factor-centric data architecture. Every uploaded document — PDF lab report, photo of a form, or discharge summary — is decomposed into atomic medical facts:
- laboratory values with dates and reference ranges;
- clinical findings from report text;
- physician prescriptions and recommendations;
- imaging data (DICOM).
These facts are not tied to a specific file — they exist as independent entities in the user profile. Glucose from a 2023 test and glucose from 2025 form one time series, not two unrelated documents.
Health Index and Biological Age
Based on accumulated data, Lissa Health calculates a health index — an aggregated assessment across key systems: metabolism, liver, kidneys, hematology, inflammation. The platform also estimates biological age using validated biomarker models (PhenoAge and extended metrics), showing how physiological status compares to chronological age.
Important: the twin does not diagnose. It helps users and clinicians see the full picture and make data-informed decisions.
Media Coverage
The digital health twin concept implemented in Lissa Health was covered by RIA Novosti, reporting on the development of a personal digital health twin powered by artificial intelligence.
Data Security
A digital health twin contains sensitive medical data. Lissa Health processes it in compliance with Federal Law 152-FZ, using TLS 1.3 / AES-256 encryption and storing data on servers in Russia. Learn more in Medical Data Security.