Impact of misdiagnosis
- % of claims with diagnostic-related features 47% 47%
- Misdiagnose due to first interpretation of test results 24% 24%
- % of misdiagnosis leading to death or permanent damage 33% 33%
Detect diseases early and accurately
Tapping into the potential of medical data may save patients’ lives without altering traditional care paths.
The healthcare sector continues to favour two fundamental concepts: prevention and efficiency. To that end, accurate early detection of medical conditions represents one of its major goals, as conditions detected early can be treated with much greater efficiency. This means less healthier patients and less healthcare expenditure.
Utilising today’s unused potential
The system’s machine learning architecture may provide clinical solutions to healthcare practitioners: by helping improve medical workflows and cutting healthcare expenditure.
The system offers valuable insights on patients’ conditions and highlight patterns, which may often remain concealed and unflagged as no direct and subject-oriented medical hints may be observed.
Striving to ensure clinical efficiency
PIT-M3D’s vision is to help promote a clinical environment, which focuses on early detection and allows for the implementation of various strategies to maximise health benefits for patients, whilst reducing costs for healthcare providers.
Our system ensures to detect all insignificant medical hints for its calculations and ultimately, flag unforeseen pathological arrangements.
More importantly, we present vital, far-reaching insights to physiological patient profiles which helps push clinical efficiency and success rates to the max.
A vast amount of physiological data is generated (typically through the regular panoply of medical tests such as blood examinations) and stored by medical institutions every day. Standard clinical interpretation of this data to diagnose conditions is only now beginning to benefit from the knowledge and abilities derived from a more systematic analytical approach.
This unique opportunity presented to the sector of systematic analysis of medical data may lead to a non-invasive tool in the successful care of patients.