AI News, Using Healthcare AI, Machine Learning for HIT Infrastructure

Using Healthcare AI, Machine Learning for HIT Infrastructure

May 01, 2018 -The engine that is healthcare is getting some pretty cool upgrades.

We know that there are technical innovations happening within the healthcare world, especially with HIT infrastructure, and we also know that there is a lot more data being created around patients and the systems they use.

Accenture points out that key clinical health AI applications can potentially create $150 billion in annual savings for the United States healthcare economy by 2026.

As their research indicates, acquisitions of AI startups are rapidly increasing while the health AI market is set to register an explosive CAGR of 40 percent through 2021.

Leveraging machine learning technology to build innovative tools for the automatic, quantitative analysis of three-dimensional radiological images.

“…We are pursuing AI so that we can empower every person and every institution that people build with tools of AI so that they can go on to solve the most pressing problems of our society and our economy,”

where cloud, AI, and machine learning all work together to help with analysis of medical imaging and deliver new kinds of healthcare services.

it comes to healthcare investment, recent findings from Transparency Market Research shows that the global healthcare natural language processing market is expected to be worth $4.3 billion by the end of 2024 as compared to $936 million in 2015.

According to the solution, it helps with the detection of specific combinations of events and underlining relations between symptoms, treatments, drugs, reactions, and biological parameters can allow automatic systems to identify potential adverse events.

As a recent HealthITAnalytics.com article points out, this could be summarizing lengthy blocks of narrative text, such as a clinical note or academic journal article, by identifying key concepts or phrases present in the source material.

When you incorporate the solutions we discussed, you’ll get the chance to create a self-operating healthcare engine that’s poised for growth and revolutionizing the services you deliver.

NLP Logix Announces Formation of WiseEye AI to Bring Computer Vision Solutions to the Healthcare Market

The same technological advances which allow data science teams to train computers to “see” and enable such applications as self-driving cars or identify people on Facebook through photos posted on the site, is being brought to a physician near you to help them diagnose disease earlier and faster.

These advances are called “deep learning” and consist of training computers to identify the patterns found in pathology slides, x-rays, MRI’s and CT scans through many repetitions presented to the computer.

The technology was recently tested in the Camelyon16 contest, which challenged teams from across the world to develop a computer program which could accurately detect cancerous tumors in breast tissue slides.

“This is a tremendous opportunity to take technology that other industries have been using for years and use it to produce higher quality image analysis tools to assist radiologists and pathologists with the detection and diagnosis of disease.” In addition to Bowling, Mike Trovato has joined the WiseEye AI team as Vice President of Sales.

48 Companies Bringing AI to Healthcare

Rarely does the word “artificial” have a positive connotation—artificial sweetener, artificial food dye, artificial meat, etc… So, why should we trust Artificial Intelligence?

Instead, AI in healthcare will be developed across multiple subsets of the healthcare industry, from drug discovery research and treatment optimizing plans all the way to being able to recognize cancerous tumors in various health screenings.

If you’re part of a team who’s pushing healthcare forward with AI, reach out—we’d love to hear from you and feature what you’re creating on this blog.

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