Machine Learning-as-a-Service for Cloud-based Healthcare Applications

Effective healthcare interoperability in the public and private sectors is mostly associated with the abilities of the services to provide a platform for data sharing among users, processes, and procedures. Lack of understanding of the healthcare status to deploy technologies makes it difficult to handle the utilization of new healthcare systems in terms of scalability and cost efficiency.

The escalation of innovations involving cloud services has resulted in various implications in the distribution of healthcare information. In this proposal, a new cloud-based platform is proposed to provide applicable data storage and management of Malaysia healthcare information.

The proposed platform is aimed to facilitate strategic implementation for practically analyze large amount of healthcare information over diverse formats. The proposed cloud- based platform also allows the implementation of machine learning algorithms as part of services within the ecosystem. This designated feature, or commonly known as machine learning-as-a-service (MLaaS), is an emerging need for accurately predicting important information from the large and complex healthcare information.

The proposed platform is expected to elevate effective healthcare information system to a level that permit predictive outcomes through smart analytic infrastructure.


Genome Analytics LLP

We are a tech-based startup focusing on the design and development of innovative solutions for healthcare applications. The solutions that we developed are built based on recent technologies, including cloud computing and machine learning algorithms. Our aim is to be a leading company in healthinformatics. To achieve this aim, we put our best efforts to deliver high quality of services.


The first nation’s Machine Learning-as-a-service based on cloud computing for healthcare applications


Google Cloud Platform, Python