News | Artificial Intelligence | May 17, 2017

Partners HealthCare and GE Healthcare Launch 10-Year Collaboration on Artificial Intelligence

Project vision includes co-development of open platform on which deep learning applications can be created, validated and seamlessly integrated into clinical workflows

Partners HealthCare and GE Healthcare Launch 10-Year Collaboration on Artificial Intelligence

May 17, 2017 — Partners HealthCare and GE Healthcare announced a 10-year collaboration to rapidly develop, validate and strategically integrate deep learning technology across the entire continuum of care. The collaboration will be executed through the newly formed Massachusetts General Hospital and Brigham and Women’s Hospital Center for Clinical Data Science and will feature co-located, multidisciplinary teams with broad access to data, computational infrastructure and clinical expertise.

The initial focus of the relationship will be on the development of applications aimed to improve clinician productivity and patient outcomes in diagnostic imaging. Over time, the groups will create new business models for applying artificial intelligence (AI) to healthcare and develop products for additional medical specialties like molecular pathology, genomics and population health.

“This is an important moment for medicine,” said David Torchiana, M.D., CEO of Partners HealthCare. “Clinicians are inundated with data, and the patient experience suffers from inefficiencies in the healthcare industry. This partnership has the resources and vision to accelerate the development and adoption of deep learning technology and empower clinicians with the tools needed to store, analyze and leverage the flood of information to more rapidly and effectively deliver care.”

The vision for the collaboration is to implement AI into every aspect of a patient journey – from admittance through discharge. Once the deep learning applications are developed and deployed, clinicians and patients will benefit from a variety of tools that span disease areas, diagnostic modalities and treatment strategies and have the potential to do everything from decrease unnecessary biopsies to streamline clinical workflows to increase the amount of time clinicians spend with patients versus performing administrative tasks. Additionally, the teams will co-develop an open platform on which Partners HealthCare, GE Healthcare and third-party developers can rapidly prototype, validate and share the applications with hospitals and clinics around the world.

With the initial diagnostic imaging focus, early applications will address cases like:

  • Determining the prognostic impact of stroke,
  • Identifying fractures in the emergency room;
  • Tracking how tumors grow or shrink after the administration of novel therapies; and
  • Indicating the likelihood of cancer on ultrasound.

The applications are being developed based on three criteria:

  1. Patient impact;
  2. Technical capability; and
  3. Market appetite.

This is to ensure that the solutions being developed are not solely dependent on the data that’s available but specifically target the top clinician pain points and the most critically ill patients. The goal is to bring the most promising solutions to market faster, so they can start making an impact for hospitals, health systems and patients globally sooner.

Spinal injury patients represent the types of cases where deep learning applications can help clinicians deliver faster, more efficient care, as the patients need to be treated immediately or run the risk of significant and permanent damage. For a single patient, a lumbar spine magnetic resonance imaging (MRI) exam may generate up to 300 images. In addition, a doctor may need to review prior scans and notes in a patient’s electronic medical record before making a diagnosis. A deep learning application could be leveraged to quickly analyze the data and determine the most critical images for the radiologist to read, shortening the time to treatment for trauma patients, and enabling the clinician to deliver more personalized and comprehensive care for all patients – critically injured or not.

“We’re evolving the healthcare system to be able to take advantage of the benefits of deep learning, bringing together hospitals, data sets and clinical and technical minds unlike ever before,” said Keith Dreyer, DO, Ph.D., chief data science officer, Departments of Radiology at MGH and BWH. “The scope reflects the reality that advancements in clinical data science require substantial commitments of capital, expertise, personnel and cooperation between the system and industry.”

Watch a VIDEO interview with MGH Center for Clinical Data Science director Mark Michalski on the development of artificial intelligence to aid radiology.

Read the article "How Artificial Intelligence Will Change Medical Imaging."

For more information: www.gehealthcare.com, www.partners.org

Related Content

LVivo EF Comparable to MRI, Contrast Echo in Assessing Ejection Fraction
News | Cardiovascular Ultrasound | June 19, 2019
DiA Imaging Analysis announced the presentation of two studies assessing the performance and accuracy of the company's...
Washington Open MRI Chooses RamSoft’s PowerServer RIS/PACS
News | PACS | June 18, 2019
Washington Open MRI (WOMRI) has selected RamSoft’s PowerServer RIS/PACS (radiology information system/picture archiving...
Double Black Imaging Announces Expanded Display Line and Ergonomic Workstation Solutions

The DBI CL8MPS from Double Black Imaging

News | Flat Panel Displays | June 18, 2019
Double Black Imaging (DBI) and their Image Systems Division are releasing their new clinical and diagnostic display...
Canon Medical Receives FDA Clearance for AiCE Reconstruction Technology for CT
Technology | Computed Tomography (CT) | June 18, 2019
Canon Medical Systems USA Inc. has received 510(k) clearance on its new deep convolutional neural network (DCNN) image...
Warm Springs Health & Wellness Center Implements Digisonics Solution for OB Ultrasound
News | Ultrasound Women's Health | June 17, 2019
Warm Springs Health & Wellness Center in Warm Springs, Ore., has selected the Digisonics OB PACS (picture archiving...
Konica Minolta Healthcare Introduces New Financing Services Program for Exa Enterprise Imaging
News | Enterprise Imaging | June 17, 2019
June 17, 2019 – Konica Minolta Healthcare Americas Inc.
M*Modal and Community Health Network Partner on AI-powered Clinical Documentation
News | PACS Accessories | June 13, 2019
M*Modal announced that the company and Community Health Network (CHNw) are collaborating to transform the patient-...
iCAD Introduces ProFound AI for 2D Mammography in Europe
News | Artificial Intelligence | June 13, 2019
iCAD Inc. announced the launch of ProFound AI for 2D Mammography in Europe. This software is the latest addition to...
A static image drawn from a stack of brain MR images may illustrate the results of a study. But a GIF (or MP4 movie), created by the Cinebot plug-in, can scroll through that stack, providing teaching moments for residents and fellows at Georgetown University

A static image drawn from a stack of brain MR images may illustrate the results of a study. But a GIF (or MP4 movie), created by the Cinebot plug-in, can scroll through that stack, providing teaching moments for residents and fellows at Georgetown University. Image courtesy of MedStar Georgetown University Hospital

Feature | Information Technology | June 13, 2019 | By Greg Freiherr
Editor’s note: This article is the third in a content series by Greg Freiherr covering the Society for Imaging In
Three Palm Software Releases WorkstationOne Version 1.8.8
Technology | Mammography Reporting Software | June 12, 2019
Three Palm Software announced the release of the 1.8.8 version of its breast imaging workstation, WorkstationOne. This...