An interactive computer-aided diagnostic software for internal medicine with more than 4,400 clinical findings to describe the profile of 612 diseases.

Biomarkers play a key role in providing precision medicine strategies. Biomarker development relies heavily on machine learning techniques such as filtering, feature extraction and predictive modeling. Because biomedical signals are high-dimensional data, they need pre-processing to filter out the noise and extract the valuable features that can be used to build predictive models for diagnosis, prognosis or treatment of diseases. 

Data science applications in medical imaging techniques including magnetic resonance imaging (MRI), X-ray, computed tomography, mammography, and so on.