Melinda Taschetta-Millane, Editorial Director
Melinda Taschetta-Millane, Editorial Director
Blog | Melinda Taschetta-Millane, Editorial Director | Artificial Intelligence| February 27, 2019

Exploring the Multi-facets of Artificial Intelligence

artificial intelligence HIMSS 2019

Artificial intelligence (AI) remains the topic of conversation at conferences and throughout the media in 2019. At the Radiological Society of North America’s (RSNA) 2018 meeting and the recent Healthcare Information and Management Systems Society (HIMSS) conference in Orlando, all eyes were on AI. Contributing Editor Greg Freiherr wrote extensive pre-, at- and post-show coverage for both regarding the trending application, and how implementing it can be achievable and the steps needed to get there, or at least get a good start.

In Freiherr’s Podcast “Hear and Now: AI and Imaging, Your Data as Strategic Asset,” Esteban Rubens, an IT infrastructure architect and executive at Pure Storage, a California company that develops flash data storage hardware and software, acknowledged that there has been “a lot of hype” around medical AI. But he stated that the hype is giving way to real progress. “We are way past the pure hype stage, because we have real things happening,” he said. “We are starting to see a lot of actual applications down to the clinical practice level of AI.”

These applications are spreading across all modalities of radiology, including women’s health. A new study published in the journal Radiology states that there is an artificial intelligence algorithm that measures breast density at the level of an experienced mammographer. The researchers said the study, the result of a collaboration between breast imagers and AI experts, represents a groundbreaking implementation of AI into routine clinical practice. Study lead author Constance D. Lehman M.D., Ph.D., from Massachusetts General Hospital (MGH) in Boston, attributed the successful clinical implementation of the AI model to two components: the availability of high-quality, annotated data evaluated by expert radiologists, and the collaborative efforts of experienced, accomplished medical and computer science professionals.

“We have to have radiologists and other physicians who understand the pressing needs of our patients and can partner with computer scientists who are experts in AI,” she said. “That is the collaboration that is going to move the field forward.”

Artificial intelligence is on the slate to be discussed in educational sessions at The Society of Breast Imaging’s annual symposium as well, where this year’s focus will be on value in breast imaging. ITN will also feature exclusive pre- at- and post-show coverage of this symposium. If you are attending, please stop by Booth #303 and tell the ITN team about the trends you are hearing about at the symposium this year.

Related Content

Konica Minolta and Shimadzu to Co-market Dynamic Digital Radiography in the U.S.
News | Digital Radiography (DR) | July 23, 2019
Konica Minolta Healthcare Americas Inc. along with Shimadzu Medical Systems USA announced a collaborative agreement to...
John Carrino, M.D., M.Ph., presents “Challenges and Opportunities for Radiology to Prove Value in Alternative Payment Models” at AHRA 2019

John Carrino, M.D., M.Ph., presents “Challenges and Opportunities for Radiology to Prove Value in Alternative Payment Models” at AHRA 2019. Photo by Greg Freiherr

Feature | Radiology Business | July 22, 2019 | By Greg Freiherr
Efforts to reform healthcare are booming, b
IBM collected a dataset of 52,936 images from 13,234 women who underwent at least one mammogram between 2013 and 2017.

IBM collected a dataset of 52,936 images from 13,234 women who underwent at least one mammogram between 2013 and 2017, and who had health records for at least one year prior to the mammogram. The algorithm was trained on 9,611 mammograms. Image courtesy of Radiology.

Feature | Artificial Intelligence | July 19, 2019 | Michal Chorev
Breast cancer is the global leading cause of cancer-related deaths in women, and the most commonly diagnosed cancer...
Paragon Biosciences Launches Qlarity Imaging to Advance FDA-cleared AI Breast Cancer Diagnosis System

Qlarity Imaging’s software is used to assist radiologists in the assessment and characterization of breast lesions. Imaging features are synthesized by an artificial intelligence algorithm into a single value, the QI score, which is analyzed relative to a database of reference abnormalities with known ground truth. Image courtesy of Business Wire.

Technology | Artificial Intelligence | July 18, 2019
Paragon Biosciences LLC announced the launch of its seventh portfolio company, Qlarity Imaging LLC, which was founded...
Graphic courtesy Pixabay

Graphic courtesy Pixabay

Feature | Artificial Intelligence | July 15, 2019 | By Greg Freiherr
Siemens has long focused on automation as a way to make diagnostic equipment faster and more efficient.
Videos | Artificial Intelligence | July 12, 2019
Khan Siddiqui, M.D., founder and CEO of HOPPR, discusses the economic advantages and costs presented by...
Videos | Digital Pathology | July 11, 2019
Toby Cornish, M.D., Ph.D., associate professor and medical director of informatics at the University of Colorado Scho
Fluke Biomedical Introduces RaySafe 452 Survey Meter
Technology | Radiation Dose Management | July 11, 2019
Radiation measurement often requires different devices for varying applications, adding to the cost and complexity of...