Moving AI forward in healthcare: intelligent algorithms as professional assistants

by The DermEngine Team on May 3, 2019

AI: at the very mention of these words, new ideas involving the major transformation of human lifestyle since the industrial revolution may come to mind.1 In the extremely fast-paced development of AI tools, their influence is set to change how health services are experienced by providers and patients alike.

Intelligent approaches in healthcare are focused on building platforms that can become strategic allies to medical professionals and complement their daily workflows with active, accurate and highly informed decision-making contributions.

1. The next generation of dermatology assistants may not be only human
AI has been evolving at its highest speed in the last decade. Regardless of the field of study, there seems to be an algorithm capable of optimizing the accuracy and efficiency of traditional processes. Healthcare practices are too being part of this transformation, as intelligent algorithms deal with more intricate workflows and higher degrees of precision.

Despite the potential of the technology itself, there is an apparent dichotomy that seems to divide the waters among healthcare providers as well as technology experts. Indeed, when it comes to AI and machine learning to support some of the most traditional tasks done by doctors, there is a high level of skepticism preventing the full adoption of this technology. However, what is important to note is that by adopting it, not all current approaches and ideas will obtain immediate validation; as with many other currently evolving technologies, there is always room for error which must first be properly addressed. The more knowledge can be extracted from practical application of AI in healthcare workflows, the better understanding there will be in terms of identifying and fixing potential pain points.

However, it’s important to  recognize that the exquisitely precise nature of AI algorithms makes them perfect candidates as personalized assistants.2 In other words, a machine learning software can be trained to learn from thousands of previously studied and documented cases for which diagnosis and treatment statistics have been collected. The more accurate data is fed to the algorithm, the more precise it will become. Doctors can then benefit by referring to an artificial colleague who has been loaded with a great wealth of information and with analytic capabilities for support in providing evidence-based decisions.

 AI can bring intelligent assistants to Dermatology
2. Assistance in dermatology as a major contribution from AI
The idea behind utilizing AI-driven technology for professional discussion and decision-making holds great value for dermatology practice models. Realistically, consulting with a trained assistant or professional colleague may be one of the safest ways to move forward in a complex diagnosis scenario. The great potential of AI to this respect comes from its learning power and its ability to handle large volumes of data with a precision unrivalled by human counterparts.

AI algorithms are able to process vast amounts of data in a repetitive fashion with a high degree of accuracy. Consulting with a trained machine that has organizational and memory capabilities greater than a human counterpart may represent the difference between a correct diagnosis or an otherwise lengthy and inefficient process. Even more so, there are no limits when it comes to which data is fed into an AI algorithm, meaning that pathology and oncology results can also be considered. This can help to establish common patterns experienced by patients when undergoing a given disease, serving as a potent tool to predict potential treatment solutions powered by the historical data based on matching patients with similar demography and clinical conditions.

AI’s contribution to this can have a revolutionary impact by efficiently storing data in a way that has never been done before. Intelligent dermatology software such as DermEngine are pioneering technologies looking to implement this approach for improved patient services. Indeed, the power of having documentation, analysis and imaging capabilities together in one single hub platform offers the chance to drive predictive strategies to benefit future cases. The more we understand about the behaviour of a disease, the easier it will be to treat it - and more importantly to prevent it. This is where AI’s participation can be paramount.

The largest contribution of AI to healthcare is in the development of optimized evidence-based decision making

Conclusion
As AI in healthcare systems have continued to rapidly evolve, it has faced shares of  skepticism, appreciation, and criticism alike. However, the more this technology develops, the clearer the role they are set to play becomes: intelligent assistants who can become best allies for doctors to make consultations much like they would with a human colleague. The level of accuracy and the potential to analyze and document vast amounts of relevant data makes this approach a feasible and highly useful one, giving AI its most noble contribution to date.

-The MetaOptima Team
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Sources
1-https://aibusiness.com
2
-https://www.nytimes.com

Topics: Dermatology AI Health Data Advanced Dermatology Artificial Intelligence in Dermatology AI In Healthcare EMR Dermatology EMR Dermatology Software Dermatology EMR Software Health Tech Big Data in Healthcare