Breakthrough innovation in X-ray image recognition
X-Doc is the X-ray image recognition platform for the early and precise diagnosis of various diseases. The objective of X-DOC is to improve the patients’ treatment and the healthcare system in general.
The HIGH price of wrong diagnosis
The wrong diagnosis leads to a high price to patients, doctors and society. Radiology errors can lead to a patients losing a chance for successful treatment when cancer or other serious disease is missed, or suffering physical and emotional distress when incorrectly diagnosed with cancer that isn’t there.
The X-DOC platform helps to reduce human mistakes and empowers doctors to be more efficient with defining the right diagnosis, significantly reducing spending of the wrong treatment and speeding up the time of patient’s recovery.
The X-DOC has the following capabilities:
- Help the doctor in more accurate diagnostic and prioritize the urgent cases.
- Gives immediate information about the patient’s condition.
- Defines other cases where the patient might need additional diagnostic/test.
- Decreases the high price and health outcomes of wrong diagnose treatment.
- Provides the accurate data and visualization of the findings for the further research.
- Available on local or cloud deployment.
The results of the field work was recognized by Manchester Metropolitan University (UK), University of Jeddah, Jeddah (Saudi Arabi), Beijing Technology and Business University (China), Central South University of Forestry and Technology (China).
How it works
are downloaded to the system
and defines pathology and diagnoses
downloaded to the hospital’s
system or printed.
- X-DOC can work either with white-black X-Rays or with colored pictures.
- X-DOC can work with additional patient’s data such as age, gender, temperature, etc. (patient’s medical card) to show the most precise accuracy in diagnostics.
- Unique neural network for each particular diagnoses united by one platform.
- Easy to scale of the neural network for each diagnosis.
- Local or cloud deployment.
- The highest accuracy (average not less than 85 %).
- Visualization of the findings (heatmap).
- User-friendly interface.