Key result
Cloud-based machine learning platform for CAD management shows efficient, accurate performance in usability testing.
A novel cloud-based platform integrating machine learning, biomechanics, and Lab-on-Chip devices for CAD management demonstrated efficiency and accuracy in usability testing.
Hypothesis-generating for integrated CAD platforms; prospective clinical validation required before adoption.
We present the architecture and the usability testing of a novel cloud-based platform, which integrates cyber-physical systems and interoperability standards enabling a clinical decision support system for risk stratification, diagnosis, prognosis and treatment of CAD. In this work multi-disciplinary human data were used for the development of machine learning and computational biomechanics based predictive models. Two Lab-on-Chip devices have been integrated into the cloud platform. A targeted RNA-panel provides the mRNA gene expression values for the stratification algorithm. The results of the usability testing demonstrate that the platform is efficient, accurate and performs all developed tasks quickly.
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Sakellarios et al. (2020) studied Coronary artery disease. Cloud-based platform for CAD management was evaluated on Usability testing. A novel cloud-based platform integrating cyber-physical systems and machine learning for CAD management demonstrated efficient, accurate, and quick performance in usability testing.
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