Leading AI companies in healthcare (Part 1)

Published
  • March 28 2017, 6:30am EDT

Companies introduce the use of artificial intelligence in healthcare

The use of deep learning, machine learning and other artificial intelligence approaches in healthcare is rapidly increasing. Over the next two days, Health Data Management highlights companies bringing a variety of approaches to the use of AI in the industry. Today’s list includes 15 companies; 25 more will be featured tomorrow.

AiCure

AiCure’s artificial intelligence visually confirms medication ingestion on any smartphone. The platform enables continuous monitoring and intervention for greater statistical power and sample size reductions in clinical trials and improved health outcomes in population health. AiCure has developed a large intellectual property portfolio and been funded by the National Institutes of Health and leading institutional investors. It provides a mobile software-as-a-service (SaaS) platform that applies machine learning, computer vision and big data to healthcare.

https://aicure.com/

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Amara Health Analytics

Amara provides real-time predictive analytics to support clinicians in the early detection of critical disease states. Early detection enables rapid response, driving better patient outcomes and lowering healthcare costs. With the acceleration toward value-based payment models, Amara says its decision support software achieves decreased lengths-of-stay, lower utilization costs and enhanced revenues. Its Clinical Vigilance for Sepsis software automatically monitors patients and issues alerts that bring immediate attention to at-risk patients.

http://amarahealthanalytics.com/

Apixio

Apixio is a data science company for healthcare that uses advanced machine learning and adaptive text analytics to give payers and providers access to insights that enable optimal decision making. Apixio’s HCC Profiler solution leverages its proprietary cognitive computing platform to drive an industry-leading productive and accurate coding workflow for MA and Commercial risk adjustment. Founded in 2009, its cognitive computing platform is built upon insights from analyzing more than 6.7 million patients and processing more than 560 million documents.

http://www.apixio.com/

Apple

Apple has boosted its presence in AI over time. In 2016, it acquired Indian machine-learning startup Tuplejump Software as it seeks to expand its expertise in artificial intelligence. Tuplejump has software that specializes in processing and analyzing big sets of data quickly.

http://www.apple.com/

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Arterys

Arterys offers cloud-based medical imaging analytics software to accelerate the transformation of data driven medicine. The company's medical imaging analytics platform leverages the power of cloud computation and deep learning to support automated post-processing, diagnostic and therapeutic decisions. Starting with cardiac MRI, Arterys now plans to leverage its platform to create other imaging applications to make medical imaging services more automated, quantitative, and useful.

https://arterys.com/

Atomwise

Atomwise is the creator of AtomNet, the first deep learning technology for novel small molecular discovery, characterized by its speed, accuracy and diversity. Research groups partner with the company to seek advantages in the scope, scale and success rates of drug discovery programs. Atomwise aims to reduce the costs of medicine development by using supercomputers to predict from a database of molecular structures which potential medicines will work, and which won’t.

http://www.atomwise.com/

Ayasdi

Ayasdi is an advanced analytics company that offers a machine intelligence platform and intelligent applications to large companies. Clients use Ayasdi to solve their big data and complex data analytics challenges and to automate formerly manual processes using their own unique data. Its machine intelligence platform combines scalable computing and big data infrastructure with machine learning, statistical and geometric algorithms and Topological Data Analysis.

https://www.ayasdi.com/

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Clinithink

The company offers an intelligent data query platform that gives healthcare and life sciences organizations the ability to extract value from unstructured data. Having recognized unstructured narrative as a rich source of information, CLiX ENRICH makes accessing this untapped resource possible to support analytics and decision making. Another platform, CLiX CNLP, was developed to enable interoperable access to and meaningful use of the volumes of existing unstructured, untapped clinical text typically locked inside electronic medical record systems and other clinical systems.

https://clinithink.com/

CloudMedx

Its clinical AI platform leverages clinical algorithms, machine learning technology, advanced natural language processing, and a proprietary clinical contextual ontology to improve clinical outcomes and lower cost. It provides precision encounters by offering real time and retrospective clinical insights at all points of care.

http://www.cloudmedxhealth.com/

Enlitic

Enlitic uses deep learning to distill actionable insights from billions of clinical cases. The company builds solutions to help doctors leverage the collective intelligence of the medical community. Enlitic uses deep learning technologies, specifically certain forms of image recognition, to harvest the data stemming from radiology images and applying it in unique medical cases.

http://www.enlitic.com/

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Flatiron Health

Flatiron Health is a healthcare technology company harnessing the power of real-world data to accelerate research and improve cancer care. The company works with healthcare providers, life sciences organizations and academic centers to collect, aggregate and analyze data for over 1.5 million active cancer patients. Today, over 250 cancer clinics and 10 of the top 12 life science companies are using its platforms. Flatiron is backed by Google Ventures, First Round Capital, Roche and others.

https://flatiron.com/

Flow Health

The company aims to bring personalized, data-driven medicine to clinicians and directly to patients, intending to discover previously unknown evidence to prevent disease onset, improve the precision of diagnosis and identify individualized treatment protocols to help clinicians make personalized medical recommendations and help people make better decisions about their health. Its mission is to advance healthcare by applying the latest artificial intelligence techniques to improve the detection, diagnosis, treatment and management of diseases.

https://flowhealth.com/

GE Healthcare

GE Healthcare provides services in medical imaging and information technologies, medical diagnostics, patient monitoring systems, disease research, drug discovery and artificial intelligence. It was recently announced that the University of California at San Francisco and GE Healthcare are teaming up to develop advanced analytics to support the next generation of clinical decision support systems hosted on a cloud platform. The project includes the development of a library of deep learning algorithms that can be embedded in decision support and aid in quicker diagnoses in acute situations such as trauma.

http://www3.gehealthcare.com/en/global_gateway

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Google Deepmind Health

The AI research branch of the company launched its Google Deepmind Health project, which is used to mine medical records in order to provide better and faster health services. Google Deepmind is able to process hundreds of thousands of medical information within minutes. Although research into such data-harvesting and machine learning is in its early phase, at the moment Google is cooperating with the Moorfields Eye Hospital NHS Foundation Trust to improve eye treatment.

https://deepmind.com/

Health Fidelity

Health Fidelity delivers comprehensive, scalable risk adjustment solutions for risk-bearing organizations that participate in Medicare Advantage, ACA, Medicaid, and Medicare ACO programs. With a combination of big data analytics and natural language processing (NLP) technology, Health Fidelity’s modern prospective and retrospective risk adjustment approaches extract insights from medical charts, changing the way risk is identified, quantified, and managed for enhanced operational, clinical, and financial outcomes.

http://healthfidelity.com/