How Is AI Changing SaaS In Dermatology?

by The DermEngine Team on Nov 29, 2018

Dermatology practices have been witness to rapid changes in technology for optimized care.1 The increased connectivity caused by widespread internet networks has allowed for the implementation of cloud services with remote accessibility, known as software as a service (SaaS) systems. This article will review the increasing expansion of SaaS in healthcare and how AI is set to make them more efficient and interoperable platforms for improved skin care services.

1. The big leap brought by SaaS in healthcare
Remote accessibility has represented one of the major advancements offered by SaaS systems. Indeed, the possibility to render information from cloud-based servers where connectivity can be achieved from nearly any place worldwide has transformed the sharing of patient data. It has also brought an added advantage: limited or even nonexistent expenses on hardware maintenance. From operational and pricing standpoints, the implementation of SaaS systems has seen such positive responses on the healthcare field given its great cost/benefit advantages. SaaS-based services in dermatology such as DermEngine are revolutionizing the way practices are operated. Continuous access to collect, analyze and share patient data has turned consultations and diagnosis into much more dynamic processes, for the benefit of doctors and patients alike.

Accessibility, automation and interoperability streamline data analysis on AI-powered SaaS. 
2. SaaS evolution driven by artificial intelligence
Artificial intelligence has become one the most rapidly advancing areas of technological development. The utilization of deep learning algorithms allows for the creation of machines able to perform highly complex tasks following thought processes much like a human being.2 So much so, that machines are already taking part in the automation of repetitive yet very precise procedures in healthcare environments, such as skin lesion image classification and diagnosis support.3

The precise and adapting nature of AI technology makes it ideal to help turn SaaS into more efficient and dedicated systems that satisfy the increasing demands of the field. To this respect, some of the areas where AI is already contributing are as follows:

a) Automation: the utilization of the AI’s human-thinking approach allows for the automation of repetitive tasks that are time consuming and tedious. Content based image retrieval (CBIR) technology qualifies machines to classify a target image based on comparisons against a library of thousands of pre-labelled images. The high specificity and low error margin makes them the ideal candidates to take on such tasks, while physicians benefit from the support to their diagnostic procedures.

b) Security: the high learning capacity of AI of pattern matching, human thinking and machine learning makes these algorithms ideal to identify and flag any type of breaching activity to security services. SaaS can benefit from target-specific strategies to guarantee patient data safeguarding.

c) Interoperability: the degree to which different SaaS systems can interact with functioning compatibility adds a great deal of value to keep a beneficial flow of data among various software and its users. The learning potential of AI-powered algorithms makes them ideal to perform high level coding and programming tasks that contribute to a better “understanding” of different platforms. Such highly operative interaction brings numerous advantages to the unhindered sharing of crucial patient clinical histories across many platforms.

AI can improve the security of SaaS systems.

Conclusion
The acquisition of SaaS systems as the operative interfaces in healthcare services has benefited from their utility, adaptiveness, affordability and centrality. However, the impact that these systems are having in daily practice is being further improved by the implementation of AI technology to their main processes. The power of deep learning algorithms to provide enhancements for automation, security and interoperability procedures are taking SaaS capabilities to unprecedented levels. As AI continues to shape the way tasks are performed, highly optimized workflows in dermatology services are expected to benefit doctors and in turn offer improved care to patients.

-The MetaOptima Team
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Sources:

1-https://www.healthcareitnews.com
2-https://svn.bmj.com
3-https://academic.oup.com

Topics: Dermatology Dermatology EMR System EMR EHR Skin Analytics Skin Imaging System Skin Cancer SaaS AI Machine Learning Artificial Intelligence