Article authored by Limor Wainstein
Cloud Computing Background
Cloud computing is an information technology paradigm that facilitates the availability of and access to shared pools of resources as services, including data storage, applications, and servers. Access to such resources is made possible via a network connection, which is typically the Internet (public cloud) but could be a dedicated, private end-to-end network connection (private cloud).
Cloud computing’s main general benefits include easy access to scalable computational power, reduced IT costs, flexibility to tailor consumption of resources based on demand, the seamless provision of IT resources as services, and greater efficiency in team collaboration.
The relevance of cloud computing in the context of healthcare and biomedicine is that this model meets the increased need for secure storage of large amounts of medical data at an acceptable cost.
There is, furthermore, a need to rapidly analyze biomedical data to assist with diagnosis and patient treatment regiments. The ease of access and availability of powerful scalable computing in the cloud helps meet the need for rapid data integration and analysis.
The term “cloud computing” can trace its roots back to a Compaq Computing business plan from 1996. However, cloud computing, understood in its modern context, didn’t enter into standard technology parlance until 2006 when Google CEO Eric Schmidt mentioned the model at a Search Engine Strategies Conference. The media began to notice this rising technology trend, and the New York Times published an article in 2007 on IBM’s proposed cloud computing strategy.
Cloud Computing Concepts
The three main architectural concepts in relation to cloud computing are Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS). A brief overview of each follows.
While the benefits of cloud computing are numerous, there are several challenges to its adoption by organizations, such as:
Cloud Computing in Healthcare & Biomedicine
A need for delivering improved patient care while meeting the growing costs of providing healthcare services necessitates prompt action by governments and healthcare providers to reduce those costs. Dudley et al demonstrated the affordability of cloud computing for studies in genomic medicine.
Furthermore, Hsieh and Hsu demonstrated that a cloud computing-based ECG teleconsultation service enhanced the quality and efficiency of medical services delivered to patients in Taiwan at a low cost of $0.12 per hour for computing power and $9.99 per month for database use.
Such studies have influenced the development of cloud computing in the context of healthcare. A 2018 report predicted that the global healthcare cloud computing market value will reach USD 44.93 billion by 2023; an increase from its $19.46 billion value in 2018.
Rocket is a cloud-based platform that facilitates the management and organization of (imaging) data and the integration of analytics tools to assist biomedical researchers, clinicians and life scientists in their daily work.
The Rocket platform, from a technological standpoint, provides three important functions:
Use Case 1: Clinical data management.
Rocket provides flexible access to clinical data relevant for specific patients. Patient data can then be processed through decision trees based on suggested regimens from professional organisations and medical literature to predict a targeted and personalized treatment strategy for individuals.
Use Case 2: Finding the optimal tool for biomedical image analysis
Rocket helps to find the appropriate tool for biomedical image analysis in different scenarios by encouraging collaboration and user input into a flexible and dynamic database of structured information. With a growing number of approaches to biomedical image analysis and the commercialization of more tools, finding the right tool for specific applications is somewhat cumbersome without an informed overview of what is available.
Additional Cloud-based Healthcare Tools
The usefulness of cloud computing in the healthcare and biomedical fields is clearly evident, and even though it’s in its nascent stages compared to other fields, the future looks bright with regards to both adoption and application of this computing model within healthcare.
If healthcare organizations and professionals take into account the challenges of cloud computing, such as ensuring a smooth cloud migration, this important application of the cloud will continue to flourish.