Ambr - all in one solution for preventive medicine

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About the Ambr solution

Harness the power of explainable AI for comprehensive multi-biomarkers analysis. Ambr integrates into doctor-patient consultations, offering:

  • Real-time visualization of clinical data

  • Precise disease probability assessments

  • Identification of key risk factors

  • Simulations of health interventions

  • Chronic disease management

  • Design of follow-up plans

  • Evidence-based & patient tailored interventions

Medical software interface displaying patient data options, including questionnaire, blood tests, and genetics tests. Features for patient insights such as simulations, assessment, reports, variable history, Ambr chat, drug interaction, and pharmacogenetic interaction are highlighted.
Line chart titled 'Probability of Risk Over Time' showing risk probability versus age, marked with percentile areas and uncertainty. The line represents current subgroup risk over ages 54 to 72, increasing over time.

We use explainable AI to provide transparency by allowing physicians to see the reasoning behind disease risk predictions, identify key patient variables influencing these risks, and their interactions.

The doctor is in control - we have no black box.

In Ambr, every suggestion is supported by direct evidence in scientific and medical literature.

Disease Guidance section listing dietary recommendations, including adherence to DASH and Mediterranean diets, higher fish consumption, higher low-fat dairy consumption, lower red and processed meat intake, with explanatory text.
Risk analysis chart showing factors that decrease or increase risk with percentages by the Ambr Institute.

Ambr synthesizes patient’s lifestyle information with laboratory results, including genetic, epigenetic, and blood biomarkers data.

We empowers the physicians and the patient to make informed decisions efficiently, enhancing outcomes and streamlining workflows.

Our AI strengthen the link between doctors & patients, and aims so support proactivity and patient’s compliance.

Our algorithms identify what intervention could decrease the probability of developing age related diseases.

We can simulate and demonstrate how these risks will change if the patient follows the health plan made by the Physician & Ambr.