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. 

Thumbnail

Intelerad launches AI initiative while announcing first clinical applications partnership for medical image analysis

Intelerad extends its partnership with Blackford to provide access to best-of-breed clinical applications and AI solutions worldwide via Blackford Platform.

Thumbnail

Fujifilm exhibits enterprise imaging solutions and artificial intelligence initiative at SIIM 2018

FUJIFILM Medical Systems U.S.A., Inc. will participate in the Society for Imaging Informatics in Medicine's (SIIM) annual meeting in National Harbor, MD, May 31 – June 2, 2018.

Thumbnail

AI diagnoses skin cancer more accurately than dermatologists

When compared to the performance of 58 dermatologists from 17 different countries around the world, AI missed fewer melanomas and misdiagnosed benign moles less often, according to a study published in the Annals of Oncology.

Thumbnail

New imaging method may shed light on diabetic retinopathy

Researchers from the University of Wisconsin-Milwaukee have used a new imaging technique to visualize cellular damage to the retina caused by diabetes. The method, tested in a mouse model, may aid in understanding diabetic retinopathy—a leading cause of blindness.

Thumbnail

British PM pledges millions to AI for improving imaging, cancer diagnosis

Theresa May, Prime Minister of the United Kingdom, has pledged millions toward government funding that will develop a "new weapon"—artificial intelligence (AI) able to improve cancer and chronic disease diagnosis.

Thumbnail

Machine learning finds rate of change—not value of ovarian cancer biomarker—indicates recurrence

Researchers utilized a machine learning algorithm to determine that a higher rate of change—rather than actual value of cancer antigen 125 (CA125)—is associated with abdominal recurrence of ovarian cancer. Findings may help identify patients most likely to benefit from imaging surveillance of the disease.

Thumbnail

AI to read 25K CT scans at London hospital for NHS clinical trial

University College London Hospital (UCLH) and the Alan Turing Institute in London have entered a three-year partnership to allow artificial intelligence (AI) to perform a variety of clinical tasks otherwise done by nurses and physicians.

Thumbnail

Experts say AI can lend a helping hand—but radiologists must learn to adapt

In a recent paper from consulting firm Deloitte, experts argue that evolving digital technology—notably artificial intelligence (AI)—has the potential to create jobs in many areas of healthcare, including diagnostic radiology.

Around the web

RBMA President Peter Moffatt discusses declining reimbursement rates, recruiting challenges and the role of artificial intelligence in transforming the industry.

Deepak Bhatt, MD, director of the Mount Sinai Fuster Heart Hospital and principal investigator of the TRANSFORM trial, explains an emerging technique for cardiac screening: combining coronary CT angiography with artificial intelligence for plaque analysis to create an approach similar to mammography.

A total of 16 cardiology practices from 12 states settled with the DOJ to resolve allegations they overbilled Medicare for imaging agents used to diagnose cardiovascular disease.