Slideshow 7 AI vendors on the leading edge in healthcare

Published
  • June 30 2017, 7:15am EDT
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Cool vendors in AI for healthcare

In its new report "Cool Vendors for AI in Healthcare, 2017," Gartner predicts a “very active and somewhat confusing healthcare AI market over the next several years.” Part of the confusion is due to “the lack of clarity in terminology and the fact that almost every vendor is capitalizing on the new bright shiny object.” The Cool Vendors selected by the research firm for this report represent some of the hottest trends in the application of AI.

Hindsait

Headquartered in Hackensack, New Jersey Hindsait “is working to apply the unique strengths of AI to major points of abrasion, operational inefficiency and missed opportunity in existing healthcare processes,” says Gartner analyst Jeff Cribbs.” An example in production today includes quality improvement, where Hindsait's AI-infused natural-language processing capabilities replace human chart abstraction and unsupervised algorithms detect patterns in the human handling of quality gaps. Hindsait also distinguishes itself with its flexibility in connecting AI to existing operations and workflow applications.”

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Medial EarlySign

Located in Kfar Malal, Israel, Medial EarlySign “uses machine learning to predict months, even years, out an individual's predisposition to certain cancers and metabolic and chronic diseases based on simple medical data, providing an opportunity to save lives and costs,” says Gartner analyst Laura Craft. “Medial EarlySign is predictive medicine in action. The company has amassed a database of 40 million geographically dispersed patient records and has created a set of AlgoMarkers that can predict the existence of conditions where early detection is critical or those that can be solved or prevented if detected early. The system works by utilizing machine learning AI to analyze millions of records, cross-referencing them with computerized medical knowledge, accumulated data and past results, known trends and similar cases to produce a patient-specific prediction.”

Zebra Medical Vision

This firm is headquartered in HaMerkaz, Israel. The number of radiology studies performed annually has increased substantially, says Gartner analyst Thomas Handler. With the aging of the population, the number of radiology studies will keep growing. “There are already too few radiologists in many countries. In September 2016, the Royal College of Radiology reported that 99 percent of radiology departments in the U.K. were unable to meet the demands they faced in 2015. One possible solution to this problem is to use computers to automatically read and diagnose medical imaging data. Zebra Medical Vision, founded in 2014, uses deep learning techniques and categorization technology on a very large training set of medical images in order to create algorithms that allow for faster and more accurate reading of x-ray studies, MRI exams and CT scans.”

Other firms to note - Enlitic

In addition to the three vendors profiled in the Gartner study, the authors discovered several other noteworthy vendors, four of which were said to deserve mention. They are: Enlitic, which uses machine learning to make medical diagnostics faster, more accurate and more accessible.

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Deep Genomics

This company uses deep learning to predict what will happen within a cell when DNA is altered by genetic variation, whether natural or therapeutic — a potential game changer in how treatments are discovered and designed.

CloudMedx and Deontics

These companies leverage cognitive computing to create personalize care paths and generate real-time clinical insights at all points of care to improve patient outcomes.