Welcome!

News Feed Item

Health Catalyst Launches Open Source Machine Learning: healthcare.ai

First open source, machine learning repository specifically for healthcare enables industrywide collaboration to advance outcomes improvement through artificial intelligence

SALT LAKE CITY, Dec. 1, 2016 /PRNewswire/ -- Use of machine learning and predictive analytics to improve health outcomes has so far been limited to highly-trained data scientists, mostly in the nation's top academic medical centers.

www.healthcatalyst.com. " border="0" alt="Health Catalyst delivers a proven, Late-Binding(TM) Data Warehouse platform and analytic applications that actually work in today's transforming healthcare environment. Health Catalyst data warehouse platforms aggregate data utilized in population health and ACO projects in support of over 30 million unique patients. www.healthcatalyst.com. " align="middle" src="http://photos.prnewswire.com/prnvar/20140217/MM66628LOGO"/>

No longer. healthcare.ai is on a mission to make machine learning accessible to the thousands of healthcare professionals who possess little or no data science skills but who share an interest in using the technology to improve patient care. By making its central repository of proven machine learning algorithms available for free, healthcare.ai enables a large, diverse group of technical healthcare professionals to quickly use machine learning tools to build accurate models. The healthcare.ai site provides one central spot to download algorithms and tools, read documentation, request new features, submit questions, follow the blog, and contribute code.

healthcare.ai was started by Health Catalyst, a leading data warehousing, analytics and outcomes improvement company that is contributing ongoing support to the open source community. Health Catalyst has used healthcare.ai to build predictive models that drive its clients' outcomes improvement efforts and span across the company's product lines. Models include but are not limited to a predictive model for central line associated blood stream infection (CLABSI), readmission models for COPD and other chronic conditions, schedule optimization, and financial predictions such as patient propensity to pay.

"Machine learning and artificial intelligence are going to transform healthcare. We are seeing amazing results and yet we are barely getting started. We are applying it to the reduction of patient harm events, care management, hospital acquired infections, revenue cycle management, patient risk stratification, and more," said Dale Sanders, Executive Vice President of Health Catalyst. "With machine learning, the data is talking to us, exposing insights that we've never seen before with traditional business intelligence and analytics. By open sourcing healthcare.ai, we hope to facilitate industrywide collaboration and advance the adoption of machine learning, making it easy for healthcare organizations to learn from and enhance these tools together, without the need for a team of data scientists. All of us have seen what open source software has achieved in other industries and we want to be a part of that in healthcare."

How healthcare.ai works

healthcare.ai makes it easy to create predictive and pattern recognition models using a healthcare organization's own data—and is unlike any other machine learning tool in the industry. The open source repository features packages for two common languages in healthcare data science—R and Python. These packages are designed to streamline healthcare machine learning by simplifying the workflow of creating and deploying models, and delivering functionality specific to healthcare:

  • Pays attention to longitudinal questions
  • Offers an easy way to do risk-adjusted comparisons
  • Provides easy connections and deployment to databases

Both healthcare.ai packages provide an easy way to create models on a health system's own data. This includes linear and random forest models, ways to handle missing data, guidance on feature selection, proper performance metrics, and easy database connections.

"We believe that machine learning is too helpful and important to be handled solely by full-time data scientists," said Sanders. "The new tools in healthcare.ai enable BI developers, data architects, and SQL developers to create appropriate and accurate models with healthcare data, without hiring a data scientist. These tools will democratize machine learning in a realm that needs it most—because everyone benefits when healthcare is made safer, more efficient and effective. And, we are not just being altruistic here. By submitting our tools and algorithms to the open source community, we and our clients will benefit from the collective intelligence that exists beyond our team of data scientists."

Participation in healthcare.ai is simple.  Interested parties can visit the site, choose either the R or Python language, read the install instructions, and follow the examples – at no cost. There is no similar platform or environment for healthcare professionals who are seeking to expand their skills and the value of machine learning to their organization.

About healthcare.ai

healthcare.ai is the world's first repository of healthcare-focused open source machine learning software. In healthcare, everyone benefits from a more efficient system and better outcomes. healthcare.ai delivers the powerful, helpful, simple tools required to transform healthcare data into actionable insights that can be used to improve outcomes. Join the healthcare.ai community today and be a part of the movement to democratize machine learning in healthcare. http://healthcare.ai.

About Health Catalyst

Health Catalyst is a mission-driven data warehousing, analytics and outcomes-improvement company that helps healthcare organizations of all sizes perform the clinical, financial, and operational reporting and analysis needed for population health and accountable care. Our proven analytics platform helps improve quality, add efficiency and lower costs in support of more than 70 million patients for organizations ranging from the largest US health system to forward-thinking, small physician practices. For more information, visit https://www.healthcatalyst.com, and follow us on TwitterLinkedIn and Facebook.

Media Contact:
Todd Stein
Amendola Communications
916-346-4213
[email protected]

Logo - http://photos.prnewswire.com/prnh/20140217/MM66628LOGO

 

 

To view the original version on PR Newswire, visit:http://www.prnewswire.com/news-releases/health-catalyst-launches-open-source-machine-learning-healthcareai-300370925.html

SOURCE Health Catalyst

More Stories By PR Newswire

Copyright © 2007 PR Newswire. All rights reserved. Republication or redistribution of PRNewswire content is expressly prohibited without the prior written consent of PRNewswire. PRNewswire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

Latest Stories
Modern software design has fundamentally changed how we manage applications, causing many to turn to containers as the new virtual machine for resource management. As container adoption grows beyond stateless applications to stateful workloads, the need for persistent storage is foundational - something customers routinely cite as a top pain point. In his session at @DevOpsSummit at 21st Cloud Expo, Bill Borsari, Head of Systems Engineering at Datera, explored how organizations can reap the bene...
Kubernetes is an open source system for automating deployment, scaling, and management of containerized applications. Kubernetes was originally built by Google, leveraging years of experience with managing container workloads, and is now a Cloud Native Compute Foundation (CNCF) project. Kubernetes has been widely adopted by the community, supported on all major public and private cloud providers, and is gaining rapid adoption in enterprises. However, Kubernetes may seem intimidating and complex ...
In a recent survey, Sumo Logic surveyed 1,500 customers who employ cloud services such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). According to the survey, a quarter of the respondents have already deployed Docker containers and nearly as many (23 percent) are employing the AWS Lambda serverless computing framework. It’s clear: serverless is here to stay. The adoption does come with some needed changes, within both application development and operations. Tha...
In his session at 21st Cloud Expo, Michael Burley, a Senior Business Development Executive in IT Services at NetApp, described how NetApp designed a three-year program of work to migrate 25PB of a major telco's enterprise data to a new STaaS platform, and then secured a long-term contract to manage and operate the platform. This significant program blended the best of NetApp’s solutions and services capabilities to enable this telco’s successful adoption of private cloud storage and launching ...
In his general session at 21st Cloud Expo, Greg Dumas, Calligo’s Vice President and G.M. of US operations, discussed the new Global Data Protection Regulation and how Calligo can help business stay compliant in digitally globalized world. Greg Dumas is Calligo's Vice President and G.M. of US operations. Calligo is an established service provider that provides an innovative platform for trusted cloud solutions. Calligo’s customers are typically most concerned about GDPR compliance, application p...
The past few years have brought a sea change in the way applications are architected, developed, and consumed—increasing both the complexity of testing and the business impact of software failures. How can software testing professionals keep pace with modern application delivery, given the trends that impact both architectures (cloud, microservices, and APIs) and processes (DevOps, agile, and continuous delivery)? This is where continuous testing comes in. D
The 22nd International Cloud Expo | 1st DXWorld Expo has announced that its Call for Papers is open. Cloud Expo | DXWorld Expo, to be held June 5-7, 2018, at the Javits Center in New York, NY, brings together Cloud Computing, Digital Transformation, Big Data, Internet of Things, DevOps, Machine Learning and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding busin...
Smart cities have the potential to change our lives at so many levels for citizens: less pollution, reduced parking obstacles, better health, education and more energy savings. Real-time data streaming and the Internet of Things (IoT) possess the power to turn this vision into a reality. However, most organizations today are building their data infrastructure to focus solely on addressing immediate business needs vs. a platform capable of quickly adapting emerging technologies to address future ...
SYS-CON Events announced today that Synametrics Technologies will exhibit at SYS-CON's 22nd International Cloud Expo®, which will take place on June 5-7, 2018, at the Javits Center in New York, NY. Synametrics Technologies is a privately held company based in Plainsboro, New Jersey that has been providing solutions for the developer community since 1997. Based on the success of its initial product offerings such as WinSQL, Xeams, SynaMan and Syncrify, Synametrics continues to create and hone in...
You know you need the cloud, but you’re hesitant to simply dump everything at Amazon since you know that not all workloads are suitable for cloud. You know that you want the kind of ease of use and scalability that you get with public cloud, but your applications are architected in a way that makes the public cloud a non-starter. You’re looking at private cloud solutions based on hyperconverged infrastructure, but you’re concerned with the limits inherent in those technologies.
Nordstrom is transforming the way that they do business and the cloud is the key to enabling speed and hyper personalized customer experiences. In his session at 21st Cloud Expo, Ken Schow, VP of Engineering at Nordstrom, discussed some of the key learnings and common pitfalls of large enterprises moving to the cloud. This includes strategies around choosing a cloud provider(s), architecture, and lessons learned. In addition, he covered some of the best practices for structured team migration an...
No hype cycles or predictions of a gazillion things here. IoT is here. You get it. You know your business and have great ideas for a business transformation strategy. What comes next? Time to make it happen. In his session at @ThingsExpo, Jay Mason, an Associate Partner of Analytics, IoT & Cybersecurity at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He also discussed the evaluation of communication standards and IoT messaging protocols, data...
With tough new regulations coming to Europe on data privacy in May 2018, Calligo will explain why in reality the effect is global and transforms how you consider critical data. EU GDPR fundamentally rewrites the rules for cloud, Big Data and IoT. In his session at 21st Cloud Expo, Adam Ryan, Vice President and General Manager EMEA at Calligo, examined the regulations and provided insight on how it affects technology, challenges the established rules and will usher in new levels of diligence arou...
Most technology leaders, contemporary and from the hardware era, are reshaping their businesses to do software. They hope to capture value from emerging technologies such as IoT, SDN, and AI. Ultimately, irrespective of the vertical, it is about deriving value from independent software applications participating in an ecosystem as one comprehensive solution. In his session at @ThingsExpo, Kausik Sridhar, founder and CTO of Pulzze Systems, discussed how given the magnitude of today's application ...
The “Digital Era” is forcing us to engage with new methods to build, operate and maintain applications. This transformation also implies an evolution to more and more intelligent applications to better engage with the customers, while creating significant market differentiators. In both cases, the cloud has become a key enabler to embrace this digital revolution. So, moving to the cloud is no longer the question; the new questions are HOW and WHEN. To make this equation even more complex, most ...