Detect and classify lung diseases promptly with computer-aided assistance
Get the diagnostics results in minutes, not hours or weeks
Why use computer-aided assistance for diagnostics?
Nowadays medical staff all over the world are under great pressure due to a significant rise in the number of patients. As proper diagnosis is crucial for further treatment and pandemic decline, healthcare providers struggle to diagnose patients both fast and correctly.
Even in normal conditions, doctors don't actually have enough time on each patient and deep diagnostics, besides each case is unique.
In case of high patient flow, precious doctor's time should be released for better patient care and decision-making. Hence a computer-aided assistant is a great solution for that challenge.
AI platform for Computer-Assisted COVID-19 and pneumonia diagnosis
Detector for COVID-19 and other lung diseases is a machine learning solution developed to speed-up the diagnostic process by classifying illnesses and calculating th probability
How it works?
Speed-up the lung diagnosis process. The solution serves as an assistant, which aims to reduce the pressure on medical staff during COVID-19 pandemic .It reduces time and effort doctors spend on diagnostic, however leaving more space for decision making and treatment.
Automatically identify and classify diseases. The solution is trained to analyse images and DICOM files. It is capable of classifying such illnesses as Pneumotorax, Pneumonia, Bacterial Pneumonia, Viral Pneumonia,COVID-19.
Recognize patients at highest risk. The solutions analyses images and as an output represents the probability of each disease it has detected. In this way it helps doctors understand the risk and make decisions about treatment and observation in time.
Easy integration, ability to be connected straight to CT/MRT;
Possibility to work in teams and share data with colleagues:
Ability to identify and analyse the probability of Pneumotorax, Pneumonia, Bacterial Pneumonia, Viral Pneumonia,COVID-19;
Ability to process and analyze wide range of image formats: png, jpeg, DICOM, etc;
Space for feedback and notes. Feedback from doctors and other healthcare professionals will be taken into consideration.