Artificial intelligence and wearables for non-invasive, predictive health monitoring.
We are developing health-focused artificial intelligence that can measure over 300 health parameters and connect to any of our devices. Get accurate health data, risk assessments for potential diseases, and personalized recommendations to improve your well-being. Connect and understand your health better through our app with a built-in health assistant.
Today, our non-invasive technology, scientific methods, artificial intelligence are showing impressive results, and measuring 300+ of health parameters. Here are some of them –
Whole blood viscosity (CP)
Blood pressure
Cardiac function index (CFI)
Glucose level
Uric acid (UA)
Fibrinogen (FIB)
Calories
Intracranial pressure (ICP)
Cholesterol and hemoglobin
Body mass index (MBI)
Blood lactic acid (Lac)
Protein, fats, carbohydrates
Resting metabolic rate (RMR)
ACCO devices for health monitoring and AI integration.
UNDER DEVELOPMENT
Pocket devices.
The range offers a wide range of health monitoring functionality and compact size for different usage situations.
An AI-powered watch for health monitoring.
The watch continuously measures and analyzes more than 300 physical and mental health parameters of the user. Non-invasive glucometer and tonometer.
UNDER DEVELOPMENT
AI HEALTHPHONE.
Smartphone with a safe optical pulse wave measurement sensor and non-invasive health monitoring functions for the user.
A patient and employee health remote monitoring platform.
Management decisions taking into account the physical and psychological state of health of employees. Remote monitoring of the main body systems of patients and employees of organizations.
ADVANTAGES
OF AI-POWERED
HEALTH
MEASUREMENTS.
High-quality measurements.
Our AI analyzes key health parameters with exceptional accuracy. Each device is equipped with a secure optical sensor that reads pulse wave signals and transmits them to the cloud for processing using artificial intelligence. The accuracy and reliability of the key data obtained have been validated through preclinical, clinical, and independent studies conducted in multiple countries.
Accessible health data for everyone.
Women’s and children’s health have unique characteristics. We have trained our artificial intelligence to take such factors into account when analyzing a user’s health. By considering all the nuances, we provide comprehensive insights into the physical and mental well-being of women and children, elevating the care of their well-being to a new level.
More than just health data.
Our artificial intelligence not only measures physical and mental health data but also includes capabilities for predicting health parameters and assessing the risk of developing various conditions (predictive or pre-symptomatic diagnostics). In addition, our Health AI Assistant provides personalized recommendations to improve the user’s physical and psychological well-being.
Research and competencies of the team.
Accofrisk works at the intersection of medicine, big data and artificial intelligence. The company's theoretical research and technologies are focused on predictive analytics, and creating products for continuous monitoring of the user's health.
Artificial intelligence.
Our competences in the field of AI lie in the development of new methods for measuring the parameters of body systems. Improving the quality of these measurements is the main priority of this work.
Health monitoring.
We measure more than 100 groups of body system parameters. In our nearest plans we are going to create and introduce a method of obtaining the parameters of the general blood analysis without blood sampling.
Healthy Aging & Longevity.
Our team is involved in the formation of standards for healthy ageing through the creation of smart health monitoring methods. We implement the concept of involving loved ones in monitoring users' health.
Prevention of diabetes.
Based on continuous measurement of glucose levels and comprehensive data. Our solutions will instantly alert the user to the first signs of diabetes. Soon we will learn how to diagnose diabetes in children.
Our partners.
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