Technology | Artificial Intelligence | March 19, 2018

Philips Launches HealthSuite Insights AI Platform for Healthcare

Online marketplace offers curated, readily available AI assets for license

Philips Launches HealthSuite Insights AI Platform for Healthcare

March 19, 2018 — Philips recently announced the launch of HealthSuite Insights, including the Insights Marketplace, to support the advancing adoption of analytics and artificial intelligence (AI) in key healthcare domains. Making their debut at the 2018 Healthcare Information and Management Systems Society Conference and Exhibition (HIMSS18), March 5-9 in Las Vegas, HealthSuite Insights gives data scientists, software developers, clinicians and healthcare providers access to advanced analytic capabilities to curate and analyze healthcare data and offers them tools and technologies to build, maintain, deploy and scale AI-based solutions. Insights Marketplace will provide the healthcare industry's first ecosystem where curated AI assets from Philips and others are readily available for license.

AI-based solutions have great potential to improve patient outcomes and care efficiency, according to Philips. However, developing and deploying AI solutions for healthcare use cases can be time consuming, resource intensive and expensive. HealthSuite Insights eases the logistical challenges of deploying AI solutions in research and clinical environments. It accelerates the development of analytics solutions, and reduces development and total cost of AI solutions.

"The quality of your AI is only as good as the quality of the data you feed into it," said Jeroen Tas, Chief Innovation & Strategy Officer Philips. "We have designed HealthSuite Insights to be used by the people who work with patient data on a daily basis and have the contextual understanding; including doctors, clinicians and hospital managers.” He added that the platform gives users the ability to bring all the relevant patient information together, curate the data and use the power of AI to support precision diagnosis, personalized therapy, early intervention and greater hospital efficiency.

The tools and technologies available through HealthSuite Insights already enable the machine learning and deep learning applications in Philips' diagnostic imaging solutions, patient monitoring solutions, and oncology and genomics offerings. Enabled by the platform, Philips leverages AI across these offerings, by combining it with other technologies and a deep understanding of the clinical, operational and personal context to augment care professionals and patients/consumers.

Philips' Insights Marketplace initially offers assets supplied by Philips – including assets developed by scientists at Philips Research. Medically validated Philips assets will be added later this year. In late 2018, the Insights Marketplace will be further expanded to include assets submitted by third parties.

AI assets built using the Insights Platform are designed to be secure regardless of the execution environment, with sophisticated identity and access management, integrated blockchain services, and data collection and management services built in. The Insights platform can be deployed on a healthcare cloud infrastructure such as the Philips HealthSuite Digital Platform, or on premise at a provider site.

For more information: www.usa.philips.com/healthcare

 

Related Content

Lunit Receives Korea MFDS Approval for Lunit Insight MMG
News | Artificial Intelligence | August 19, 2019
Lunit has announced Korea Ministry of Food and Drug Safety (MFDS) approval of its artificial intelligence (AI) solution...
Artificial Intelligence Could Yield More Accurate Breast Cancer Diagnoses
News | Artificial Intelligence | August 13, 2019
University of California Los Angeles (UCLA) researchers have developed an artificial intelligence (AI) system that...
The CT scanner might not come with protocols that are adequate for each hospital situation, so at Phoenix Children’s Hospital they designed their own protocols, said Dianna Bardo, M.D., director of body MR and co-director of the 3D Innovation Lab at Phoenix Children’s.

The CT scanner might not come with protocols that are adequate for each hospital situation, so at Phoenix Children’s Hospital they designed their own protocols, said Dianna Bardo, M.D., director of body MR and co-director of the 3D Innovation Lab at Phoenix Children’s.

Sponsored Content | Case Study | Radiation Dose Management | August 13, 2019
Radiation dose management is central to child patient safety. Medical imaging plays an increasing role in the accurate...
Lake Medical Imaging Selects Infinitt for Multi-site RIS/PACS
News | PACS | August 09, 2019
Infinitt North America will be implementing Infinitt RIS (radiology information system)/PACS (picture archiving and...
Half of Hospital Decision Makers Plan to Invest in AI by 2021
News | Artificial Intelligence | August 08, 2019
August 8, 2019 — A recent study conducted by Olive AI explores how hospital leaders are responding to the imperative
NetDirector Launches Cloud-based PDF to DICOM Conversion Service
News | PACS | August 08, 2019
NetDirector, a cloud-based data exchange and integration platform, has diversified their radiology automation options...
ScImage Introduces PICOM ModalityGuard for Cybersecurity
Technology | Cybersecurity | August 07, 2019
ScImage Inc. is bridging the gap between security and functionality with the introduction of the PICOM ModalityGuard....
Artificial Intelligence Improves Heart Attack Risk Assessment
News | CT Angiography (CTA) | August 06, 2019
When used with a common heart scan, machine learning, a type of artificial intelligence (AI), does better than...
Montefiore Nyack Hospital Uses Aidoc AI to Spot Urgent Conditions Faster
News | Artificial Intelligence | August 05, 2019
Montefiore Nyack Hospital, an acute care hospital in Rockland County, N.Y., announced it is utilizing artificial...
The top piece of content in July was a video interview explaining how Princess Margaret Cancer Center is using machine learning to create automated treatment plans. This was a hot topic at the American Association of Physicists in Medicine (AAPM) 2019 meeting in July.

The top piece of content in July was a video interview explaining how Princess Margaret Cancer Center is using machine learning to create automated treatment plans. This was a hot topic at the American Association of Physicists in Medicine (AAPM) 2019 meeting in July. 

Feature | August 05, 2019 | Dave Fornell, Editor
August 5, 2019 — Here is the list of the most popular content on the Imaging Technology New (ITN) magazine website fr