Artificial intelligence is making itself invaluable in a variety of industries, including healthcare. With this in mind, Becker’s Health IT and CIO Report offers five useful terms to add to your AI playbook:
- Artificial intelligence: Intelligent behaviors commonly associated with humans but exhibited by machines and applied to tasks like problem-solving, automatically completing forms or parsing medical images to recommend diagnoses. In theory, true AI should be able to think like and interact with other humans seamlessly.
- Machine learning: An application of AI that uses algorithms to find patterns in data without instruction. Machine learning automates a system’s ability to learn, so it can improve from experience without being programmed for each l task it completes. A machine learning model is “trained” on relevant examples from diverse data sources.
- Natural language processing: A computer’s attempt to interpret written or spoken language. Because language is so complex, computers must carefully parse vocabulary, grammar and intent while allowing for variation in word choice when processing language, which is why programmers often take multiple AI approaches to natural language processing.
- Robotic process automation: A type of AI that entails training software algorithms to mimic how an employee would complete a specific task. These tools are often equipped with computer vision, or the ability for a machine to perceive and interpret visual or text-based imagery. Robotic process automation models are trained by “watching” the human user perform that task and then directly repeating it.
- Turing test: The original test of a machine’s ability to successfully converse with a human evaluator in such a way that a third party wouldn’t be able to determine which was the human and which was the machine. Developed by Alan Turing in the 1950s, the Turing test picks out the most sophisticated AI from AI that is merely a simulation of human intelligence. In other words, AI that passes a Turing test is indistinguishable from a human.
The article goes on to say:
Some of the processes organizations want to automate are lengthy and complex, and often consist of numerous steps.
Automating these tasks can free up employees’ schedules so they can dedicate time to activities that require critical thinking, problem solving and creativity, thereby allowing organizations to scale their workforce and ease clerical burdens for employees.
With automation, healthcare organizations can accomplish more and scale their workforces. Understanding how AI works is just the first step to process improvement.
You heard the AI message conveyed at OrboGraph’s 2018 Conference, and you’ll learn how OrboGraph is operationalizing AI and Deep Learning Technologies at the 2019 Healthcare and Check Payment Technology Conference (May 20-21, 2019, at the Charlotte Marriott City Center).