Around a third of all initial diagnoses are wrong
A vast amount of physiological data (such as blood test results) is being generated everyday by the healthcare industry.
In most cases this data is used within the confines of the care of the patient.
Aggregating the data for analysis may represent a very significant opportunity for the sector but the complexity of handling extremely large quantity of data may lead to solutions offering limited use as they may be inaccurate or limited in scope.
Accurate diagnostic technology is the best tool to address the misdiagnosis crisis in the healthcare sector.
The PIT-M3D research demonstrates that most human conditions and diseases may be identified, diagnosed and predicted looking at individual’s physiological data.
We aim to offer a technology which can algorithmically diagnose and detect the vast majority of known human diseases and conditions with a very high accuracy and at an extremely early stage, even when symptoms may not be expressed for years.
Combining machine learning and advanced statistical analysis, our system detects minute changes in a patient physiology and compare them to specific identified patterns in our large library of electronic medical records.
Patients will benefit from quick and precise diagnostic, which allows practitioners to have more time for treatment. The correct treatment is applied earlier and ineffective treatments are reduced significantly.
Data derived from routine check-ups contains a lot of potential information that our System can exploit to identify pre-chronic stage patients, such as melanoma development.
Real-time evaluation for healthcare providers, other institutions or private second opinion seekers.
Independently developed medical validation processes automatically validate prediction and detection models in real-time.
Our System can adapt to and be integrated with any existing care protocol. The process of integration is easy and results in automated processes.