A Cloud-based Risk Stratification Platform Cardiovascular Disease, Depression and Comorbidities *

There is strong clinical evidence that patients with depression have a high probability to exhibit cardiovascular disease (CVD) and vice versa. Thus, it is important to accurately identify these patients to provide optimal management of the comorbid conditions. Although the existing literature focuses on the development of artificial intelligence (AI) models for the diagnosis of CVD and/or depression, there is not currently any reported tool or system which integrates such models for clinical practice. In this work, we present a cloud-based platform to enable the easier, accurate, and cost-effective diagnosis of CVD and depression. The cloud-based platform is an integrated cloud-enabled computing unit that provides the execution of artificial intelligence computing algorithms along with data exchange services by utilizing the REST (Representational State Transfer) architecture. The platform enables the seamless and transparent interfacing of AI models and applications for the end-users. During the development a variety of state-of-the-art technologies and architectural models were integrated through a Payara Application Server, the Python programming environment (version 3) and a MySQL database server. Java SDK 11 was used for developing the full-stack API of the user interfaces and the back-end logic including the REST interfaces. The platform is hosted on a Linux Virtual Machine (VM). The development resulted in a cost-effective, accurate and efficient tool for the risk stratification of depression and CVD.Clinical Relevance- This is a state-of-the-art cloud-based platform for the risk stratification of CVD and depression. Example: Cardiologists and psychiatrists can use this platform to identify patients with CVD and depression and then prescribe more detailed examinations.