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.

AI model gets helpful heart assessments out of nongated CT scans
"Using AI for tasks like CAC detection can help shift medicine from a reactive approach to the proactive prevention of disease," one researcher said.
Led by notable names in radiology, imaging AI firm HOPPR raises nearly $32M
Founded in 2019 and based in Chicago, the vendor offers a “leading” infrastructure platform for building, refining and deploying large-scale AI models in medical imaging.
Healthcare AI today: Dangerous LLMs, self-training AI—and is AI good for what ails healthcare?
If an individual is at all susceptible to mental unwellness, overuse of a talkative LLM could push him or her over the edge. Maybe literally.
Could the metaverse be the new radiology education classroom?
According to new data, the simulated virtual environment may be just as effective of a setting as the classroom for problem-based learning.
ChatGPT's medical advice may be deterring women from necessary imaging
The LLM’s responses may be misleading in certain situations, which could pose problems for patients who trust the medical advice it provides.

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

VIDEO: How hospital IT teams should manage implementation of AI algorithms

Julius Bogdan, vice president and general manager of the HIMSS Digital Health Advisory Team for North America, explains considerations for healthcare IT teams on the implementation of artificial intelligence (AI).

VIDEO: Validation monitoring for radiology AI to ensure accuracy

Bibb Allen, MD, FACR, Chief Medical Officer of the American College of Radiology (ACR) Data Science Institute, and former ACR president, explains how hospitals or radiology departments can conduct quality assurance assessments on artificial intelligence algorithms they adopt to ensure they are accurate.

Machine learning model uses MRI data to identify candidates for liver transplant

When applied to MRI and clinical features, different machine learning models were recently shown to reliably predict post-treatment recurrences of hepatocellular carcinoma.

Nuance and Covera join forces to improve radiology quality ‘at scale’

PowerScribe purveyor Nuance is partnering on widescale care improvement with a healthcare AI startup that made its name showing Walmart where, and where not, to send its employees for high-accuracy radiology.

Deep learning system outperforms rads in brain tumor identification and classification

The new findings findings represent “a step toward improved tumor diagnoses," according to authors of a new study published in JAMA.

An overview of artificial intelligence (AI) in radiology with Keith Dreyer with the ACR. Images shows a COVID-19 lung CT scan reconstruction from Siemens Healthineers. #AI #radAI #ACR

VIDEO: Overview of radiology AI by Keith Dreyer

Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute Chief Science Officer, explains the state of AI in radiology in 2022.

Example of a radiology diagnostic aid artificial intelligence (AI) algorithm with Lunit's mammography cancer lesion detection system.

VIDEO: Segmenting the Radiology Artificial Intelligence Market by Function

Keith J. Dreyer, DO, American College of Radiology (ACR) Data Science Institute chief science officer, breaks down radiology AI down into 4 areas and discusses where these areas stand with regulatory approval.

New national board forms, opens training course in radiological AI

An educational outfit has sprung up to equip nonphysicians working in radiology—chiefly administrators, business managers and technologists—with radiologist-level fluency in AI.

Artificial Intelligence

AI model gets helpful heart assessments out of nongated CT scans

Led by notable names in radiology, imaging AI firm HOPPR raises nearly $32M

Healthcare AI today: Dangerous LLMs, self-training AI—and is AI good for what ails healthcare?

Could the metaverse be the new radiology education classroom?

ChatGPT's medical advice may be deterring women from necessary imaging