Airtificial intelligence solutions for healthcare

Artificial intelligence saves time for specialists by providing data-driven decision-making and delivers more personalized patient care

Computer vision analyses images and video, machine learning algorithms manage large amount of data, natural language processing structures texts

Machine learning has proven track of being efficient in predicting equipment failures for years. It's time we used artificial intelligence to improve the quality of life for people as well

What we do:

  • Automatic real-time monitoring of patients' condition
  • Selection of the optimal operating mode of the equipment
  • Analysis of images, video and other data using neural networks to detect diseases or complications
  • Smart knowledge base instead of a handbook

Our advanteges:

  • Experience in developing AI solutions

    We have implemented both R&D projects and complex solutions wich improve the condition of patients

  • Working with anonymized data

    We are serious about the reliability of personal data and its possible leakage, therefore we work only with anonymized data

  • Cyber security expertise

    With extensive experience in the field of cybersecurity, we can guarantee complete reliability and safety of data to our clients

How we work

Development of an entire product on average takes up to 6 months.

Data Exploration and Preparation 1 month
Proof of Concept 1 month
Optimizing machine learning models 2 month
Implementation, testing and finalization of the solution 2 month
User interface development 2 - 4 month
  • 1 month

    Data Exploration and Preparation

  • 1 month

    Proof of Concept

  • 2 month

    Optimizing machine learning models

    2 - 4 month

    Implementation, testing and finalization of the solution

  • 2 month

    User interface development

Cases

AI medicine platform
starbucks

Machine learning for mechanical ventilation

Our web and mobile app provide data about patients enriched by machine learning algorithms.
The solution detects mechanical ventilation asynchronisms, predicts patient's future condition and gives recommendations to clinical specialists for optimal regime of equipment.
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