The current imaging interpretation model undoubtedly has reached its breaking point due to increasing volumes and fewer radiologists. The time is now to solve this systemic imaging interpretation issue.

New York-based startup Ezra recently received FDA clearance for an AI tool it plans to use to launch “the world’s first 30-minute full body MRI scan.” The tool, named Ezra Flash, enhances the quality of MR images so that radiologists can detect cancer earlier.

Oxos Medical recently raised $23 million in Series A funding. The company’s handheld X-ray devices are meant to replace C-arms, which are the leading medical imaging technology. The devices are portable are require little training to use, which is key considering the massive dearth of radiologists entering the field.

The potential of ChatGPT is exciting. Radiologists have come a long way on the AI journey. What started as a fear from some that AI would replace us, has evolved to a more nuanced understanding that AI’s greatest contribution in medical imaging is to make us better radiologists.

Recently, scientists shared new findings that may indicate the inner core of the earth has […]

Medical device manufacturer iCAD entered into a development and commercialization agreement with Google Health, in which it will integrate Google’s mammography AI technology into its suite of breast imaging AI products. The agreement marks Google’s first commercial partnership to deploy its breast imaging AI model into clinical practice.

Many of the efforts to address healthcare’s burnout crisis have centered on money, such as hiring and retention bonuses, but that isn’t sustainable. Providers don’t have the means to keep throwing money at the problem forever, so they should focus more on creating a workplace culture where employees feel valued and supported.

Google Cloud unveiled a new product suite to make medical imaging data more interoperable and useful via artificial intelligence. Hackensack Meridian Health has begun using it to detect metastasis in prostate cancer patients earlier, and Hologic is using it to strengthen its diagnostic platform that screens women for cervical cancer.

Aidoc, a Tel Aviv-based startup providing software to help radiologists triage scans, closed a $110 million funding round on Thursday. The company will use the money to expand its AI platform and develop care coordination tools for various specialties instead of focusing solely on radiology.

Just after exiting stealth with $62.5 million in Series A and B financing, Sirona Medical plans to leverage Nines’ AI technologies to provide a comprehensive digital solution for radiologists.

The company makes software to spot diagnostic errors in radiology and route patients to centers of excellence.

Aidoc, a Tel Aviv-based startup building a suite of decision support tools for radiologists, raised $66 million in funding. The company plans to use the funds to build out and market its suite of radiology solutions. 

In a review of 130 FDA-cleared AI tools, researchers found that the vast majority of them relied on retrospective studies. Most of the developers also didn’t share information on how many sites the algorithms had been tested in, or how they performed in different patient demographics. 

The health system and tech giant are more than a year into their 10-year collaboration. As their partnership evolves, the organizations are looking to create an “AI factory” — an assembly line of AI solutions that are developed at scale and incorporated into clinical workflows.

The startup struck a partnership with Premera Blue Cross to identify radiologists with low rates of misdiagnoses for its Centers of Excellence program. The benefit will be available to Premera’s fully insured members and self-insured companies.

Nines received 510(k) clearance for a system that monitors CT scans for likely cases intracranial hemorrhage and mass effect, two conditions associated with strokes. The system prioritizes these cases for review from radiologists, letting patients receive a diagnosis faster.  

Catholic Health Services of Long Island is aiming to deploy an AI algorithm next week to help ER doctors determine whether a patient presenting Covid-19-like symptoms should be admitted to the ER or sent home.

A retrospective study published in Nature shows Google’s DeepMind AI outperformed radiologists in detecting breast cancer. But it won’t be replacing them anytime soon.

Nines, a teleradiology company using machine learning to triage important cases, raised a $16.5 million funding round led by Accel and 8VC.

Most AI-powered startups in radiology tackle an image problem, but Rad AI have been focused on a workflow problem by automatically generating the impressions section of a radiologist’s report, which is a summary of the report’s other sections.

At a time when artificial intelligence is gaining ground in healthcare, especially in radiology, it is important to understand the varied metrics being used to evaluate the technology.

The regulatory decision comes just a few weeks after the FDA cleared the company’s pulmonary embolism product.

The FDA decision, which builds on a prior approval of the company’s algorithm for the detection of intracranial hemorrhages through CT scans, is part of a larger vision sketched out by CEO Elad Walach of plugging new algorithms into the Aidoc system to create a new standard of care in radiology.

Aidoc pitches its product as a way to more quickly scan and detect potential issues in medical images.

Updates to the company’s Clara healthcare platform are trying to make it easier for clinicians to train and adapt deep learning algorithms, while also making the implementation process smoother.

The New York City-based company is currently focused on bringing its approach to the radiology field.

During a panel at the MedCity INVEST Twin Cities conference leaders from the payer, provider and investor spaces spoke about how to actually drive adoption of AI tools in the clinical system.

AI-for-radiology advances are being developed by and in partnership with radiologists to improve physician workflows and patient care with real-time assessment, point-of-care interventions, faster exam times, and more confident diagnoses.

The Tel Aviv, Israel-based startup is leveraging artificial intelligence and deep learning to improve the radiology workflow. Its technology pinpoints abnormalities in a medical image.

Rethinking radiology design and imaging centers with a patient-first approach can lead to meaningful strides in accomplishing the overall goals in value-based care.