Artificial Intelligence Will Change Healthcare as We Know It

8/26/2019

Artificial Intelligence Will Change Healthcare as We Know It

Arti cial Intelligence Will Change Healthcare as We Know It usm systems Aug 26 ¡ 3 min read

Machine learning and deep neural networks have made significant advances in artificial intelligence.

Major AI applications in health care include diagnostics, robotic surgeries, and virtual nursing assistants.

Healthcare AI is expected to reach a value of $ 6.6 billion by 2021.

The adoption of AI is expected to reach the U.S. by 2026 The healthcare industry saves 150 billion a year.

As Artificial Intelligence (AI) improves, the healthcare industry may move toward another high-tech makeover (although it continues to adapt to the advent of electronic health records systems and other healthcare IT products). Are AI applications new to every sector of the health care industry? Many experts believe that this is inevitable and will come sooner than you think.

What is Artificial Intelligence?

AI can be defined as computers and computer software capable of intelligent behavior such as analysis and learning. It is a broad category at the brink of technological development, growing and changing every day.

Machine learning and neural networks Machine learning is the foundation of modern AI and is an algorithm that allows computers to learn independently without necessarily following explicit programming.

As machine learning algorithms face more data, the performance of algorithms improves. https://medium.com/@usmsystems23/artificial-intelligence-will-change-healthcare-as-we-know-it-bc936ad9a68c

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8/26/2019

Artificial Intelligence Will Change Healthcare as We Know It

Deep learning is a subset of machine learning that works the same way with a little twist.

Deep learning takes it a step further, making inferences based on previously encountered data. In other words, deep learning allows the AI app to make its own conclusions. It works through an artificial neural network, which is a set of machine learning algorithms. A neural network resembles the human brain, with a series of “neurons” that “fire” when certain stimuli (in this case, data) are present.

“Traditional machine learning solutions are not cognitive; they are trained from data but do not have the ability to jump beyond missing or broken data and formulate a hypothesis about potential actions,” said AJ Abdullah, CEO of Beyond Limits. “Machine learning is effective in detecting what the machine does, but it fails when unexpectedly encountered.”

In order to take artificial intelligence to the next level, developers must emphasize both reductionism and inductive reasoning, and simulate those cognitive models in the machines they create. The advantage of dynamic, deep learning solutions is that they can explain their reasoning and conclusions, which is the main purpose of complex decision making.

How is AI used in health care?

AI is still a relatively new technology, especially in the health care industry, which is still in its infancy. As AI and machine learning tools become more sophisticated, their use cases expand; However, according to John Fraunfelter, chief medical information officer at Jvion, the adoption of AI is low.

“We are still in the hype stage where a lot of organizations are trying to understand how this fits into the overall strategy,” says Fraunfelter. “Early AI has seen … greater emphasis on pattern recognition for billing processes. It has evolved to make deep machine learning more sophisticated and increase the power of big data.”

Modern AI applications have a wide range of use cases ranging from cybersecurity to radiographic imaging, Fraunfelter said. As AI applications continue to improve, the entire healthcare industry is undergoing a change. Here are some of the major ways AI is expected to shape health care in the coming years.

Diagnostics https://medium.com/@usmsystems23/artificial-intelligence-will-change-healthcare-as-we-know-it-bc936ad9a68c

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Artificial Intelligence Will Change Healthcare as We Know It

AI is great at categorizing data, especially once it is exposed to large amounts of data on this topic. This creates a great promise for AI when it comes to diagnostics — medical imaging analysis and patient medical records, genetics and more to improve diagnostic outcomes. In addition, AI tools can use such information to create unique therapeutic strategies and provide recommendations to clinicians.

“The really interesting developments are in the clinical field,” says Fraunfelter. “Clinical Prescriptive Analytics is probably the closest AI to support direct patient care in 2019.”

Robot-assisted surgery Robotic surgeries allow surgeons to use smaller tools and make more precise cuts.

Surgeons (and patients) can benefit from AI by combining medical records with realtime data during operations, as well as drawing data from previous successful surgeries of the same type. Accenture, a technology consulting firm, plans to launch an AIenabled, robot-assisted operation in the U.S. by 2026. The healthcare industry is estimated to save $ 40 billion a year.

Virtual Nursing Assistants Think of virtual nursing assistants like Alexa for your hospital bedside. These virtual assistants reflect the typical behavior of the nurse by assisting patients with their daily routines, taking medication or appointments, answering medical questions, and more.

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