Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks.

Humana expands use of automated prior authorization software into diagnostic imaging
The Louisville, Kentucky-based payer first partnered with vendor Cohere Health in 2021 to launch a pilot program in 12 states.
Use of AI in radiology revenue cycle management
Dave Walker, senior director of revenue cycle, Radiology Associates of North Texas, explains how his practice uses artificial intelligence for revenue cycle management during the Radiology Business Management Association (RBMA) 2024 meeting.
GPT-4 can detect radiology report errors at the same rate as members of the specialty
“This efficiency in detecting errors may hint at a future where AI can help optimize the workflow within radiology departments," a lead author of the study said.
Semiautonomous AI shows potential to reduce false positives, unnecessary procedures and medical expenses
Scientists developed the deep learning algorithm using a set of over 123,000 digital mammograms (including 6,100-plus cancer cases).
GE HealthCare finalizes acquisition of Cleveland-based provider of AI imaging-analysis software
The company plans to integrate MIM Software's radiology and nuclear medicine solutions into its advanced-visualization product line.

probably benign abnormalities on mammogram

Google Health partners with iCAD in commercial AI imaging push

The deal is the first commercial partnership for Google Health to introduce its breast imaging AI into clinical practice.

December 1, 2022

RadNet and Google Health join forces to use AI for lung cancer screening

Aidence will license, develop, and validate Google Health’s existing AI research module, hoping to offer better differentiation between benign and malignant lung nodules at an early stage.

November 29, 2022

Chest X-ray. Using an explainable artificial intelligence (AI) model, researchers were recently able to accomplish highly accurate labeling on large datasets of publicly available chest radiograph X-rays..

New AI model calculates risk of heart attack or stroke using a single X-ray

“This type of screening could be used to identify individuals who would benefit from statin medication but are currently untreated," one specialist said. The full analysis will be presented at RSNA 2022 in Chicago.

November 28, 2022

Julius Bogdan, vice president and general manager of the Healthcare Information and Management Systems Society (HIMSS) Digital Health Advisory Team for North America, explains considerations for healthcare system information technology (IT) management teams on the implementation of artificial intelligence (AI). He also discusses ideally how AI should be integrated into medical IT systems, and some of the issues AI presents in the complex environment of real-world patient care." #AI #HIMSS

Radiologist examines AI's potential to transform medical imaging

Linda Moy, MD, the first female editor of Radiology, said that artificial intelligence can help address a multitude of issues today’s radiologists face, but obstacles do remain.

November 28, 2022

Charles E. Kahn, Jr., MD, MS, Editor of the the RSNA journal Radiology: Artificial Intelligence, and professor and vice chair of radiology at the University of Pennsylvania Perelman School of Medicine, discusses trends in radiology medical imaging AI. He has been heavily involved in radiology informatics and has seen up close the evolution of radiology toward deeper integration with AI. #RSNA22

VIDEO: An updated look at the use of AI in radiology

Ahead of RSNA 2022 in Chicago, Charles E. Kahn, Jr., MD, MS, spoke with Radiology Business about how AI is being used by radiologists—and how that may evolve in the years ahead.

November 28, 2022

Aidoc, Avicenna, Viz.ai and 10 more imaging AI names in the pre-RSNA news

Also worth a look: the ACR Data Science Institute’s AI Central, updated this week with detailed information on imaging AI products that have been cleared by the FDA.

November 23, 2022

Experts ID imaging biomarkers in kids with ADHD

The study's authors explained how MRI results can be used to help identify children with ADHD—and how these findings could be used in the AI algorithms of tomorrow. The team will be presenting its findings at RSNA 2022 in Chicago.

November 22, 2022

Amazon is acquiring One Medical in a $3.9 billion deal

Amazon marshals partners, providers behind major move into medical imaging

Cloud giant Amazon Web Services is expanding its 1½ -year-old HealthLake data-management service in two imaging-specific directions. In the process it’s drawing vocal buy-in from healthcare providers as well as imaging vendors.

November 16, 2022

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Cardiovascular Business

Medicare drops AUC requirement for advanced imaging, ASNC celebrates

"This was an unneeded burden, which was solely adding to the administrative hassles of medicine," said American Society of Nuclear Cardiology President Larry Phillips.

Cardiovascular Business

Cardiology, radiology groups urge insurance provider to rethink imaging policy

SCAI and four other major healthcare organizations signed a joint letter in support of intravascular ultrasound.

Cardiovascular Business

Radiology AI company gains FDA clearance for new CT offerings focused on PE, stroke

The newly approved AI models are designed to improve the detection of pulmonary embolisms and strokes in patients who undergo CT scans.

Artificial Intelligence

Humana expands use of automated prior authorization software into diagnostic imaging

Use of AI in radiology revenue cycle management

GPT-4 can detect radiology report errors at the same rate as members of the specialty

Semiautonomous AI shows potential to reduce false positives, unnecessary procedures and medical expenses

GE HealthCare finalizes acquisition of Cleveland-based provider of AI imaging-analysis software

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