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AI and personalized medicine to raise the bar in radiology reporting New innovations could provide myriad benefits to clinical workflow

The exam room of the future: Nuance unveils AI-based clinical documentation product at HIMSS Improving patient experience and freeing up physicians

HIMSS Analytics releases new model to help adopt enterprise imaging Eight-stage DIAM model helps organizations track their progress

Bitfury teams with MDW and Longenesis to create blockchain ecosystem for medical imaging Uphold, distribute and safeguard medical and diagnostic imaging

Hologic launches Unifi Analytics to curb mammo downtime Predicting tube failures before they happen and setting performance benchmarks

My observations from the HIMSS meeting The Jacobus Report

Health IT Product Showcase A few of the new solutions improving hospital workflow

Imaging IT market insights The analysts at MD Buyline provide tips for navigating the market

Moffitt Cancer Center secures radiology machines by ditching anti-virus software Speeding up software without compromising cybersecurity

Siemens focuses on digitalization at HIMSS Its expanded digital service portfolio will be on display

Artificial intelligence’s role in incubating new healthcare solutions


AI equals real results
Depending on the industry, AI delivers different types of results. In the healthcare industry, AI solutions can assist in improving health outcomes, especially when it comes to breast imaging.

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According to Breastcancer.org, nearly one in eight U.S. women will develop invasive breast cancer during her lifetime. However, two-thirds have the potential to be saved through early detection and progressive treatments. In response, many medical facilities worldwide are turning to Digital Breast Tomosynthesis (DBT) technology solutions as their preferred method for screening and diagnostic mammography in order to do just that – detect and diagnose women with early-stage breast cancer.

But just like all technology, there are also some challenges radiologists face when utilizing DBT. For example, detection of breast cancer using DBT involves interpretation of massive data sets, which can be extremely time consuming for radiologists. A 3D mammogram, or DBT, produces hundreds of images, while 2D digital mammography exams produce only four images. While DBT ultimately provides greater clarity and detail, it also requires radiologists to spend significantly more time reviewing and interpreting breast exams.

However, this is where technology comes into play. Radiologists can leverage innovative AI and deep learning solutions to help reduce their DBT interpretation time and improve reading workflow. This is due to the capabilities of particular AI solutions, as some tools can automatically highlight areas for radiologists that might appear concerning, calling attention to spots that might need to be reviewed more cautiously. These capabilities are especially imperative for radiologists today, as many report feeling burnout.

Although more research needs to be done on AI, in the medical imaging industry its clear these solutions are fundamentally changing the way radiologists and other healthcare providers do their jobs. In order for providers to overcome their concerns associated with AI, they must first carefully research and consider the right AI solution for their individual needs. As the healthcare industry as a whole continues to transform, it’s easy to believe that providers who utilize and understand the unique capabilities of AI solutions will perform above the rest.

Jeffrey Hoffmeister
About Jeffrey Hoffmeister: As VP, medical director at iCAD, Jeffrey has participated in developing mammographic AI solutions for 25 years. He has provided clinical insight to engineering and marketing teams and managed the design and implementation of clinical studies for FDA approval of mammographic AI products, from iCAD’s first mammography CAD product, SecondLook, in 2002 to iCAD’s most recent digital breast tomosynthesis AI solution, PowerLook Tomo Detection. iCAD, a global leader in medical technology providing innovative cancer detection and therapy solutions, is the manufacturer of the first and only FDA-approved concurrent-read cancer detection solution for breast tomosynthesis, iCAD’s PowerLook Tomo Detection. Utilizing a trained algorithm developed through deep learning, the system automatically analyzes each tomosynthesis plane and identifies suspicious areas. These images are then blended into a 2D synthetic image, providing radiologists with a single, highly sensitive, enhanced image from which they can easily navigate the tomosynthesis data sets.

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