You are here

Artificial Intelligence

 

Machine learning and artificial intelligence (AI) are two hotly discussed topics in healthcare, but radiologists tend to fear a future where computers replace people. But that fear may be unwarranted, according to one expert.

According to survey results recently published online in the Journal of the American College of Radiology, more than one-third of radiologists lack exposure to artificial intelligence (AI) educational material and resources. Additionally, most trainees' desire to learn about or pursue diagnostic radiology is hindered by AI's role in medicine.  

A University of Saskatchewan team has created a deep learning technique that demonstrated enhanced de-noising capabilities in low-dose CT (LDCT) imaging, resulting in little resolution loss and better performance, according to a study published in the Journal of Digital Imaging.

Radiation therapy is an integral part of many cancer treatments. Ideally, doses are focused on the observable tumor while leaving surrounding organs unaffected, but determining the figuration of tumors and organs-at-risk is done manually—a time consuming and, at times, imprecise task for radiologists.

According to a Feb. 13 press release, the FDA announced clearance for the marketing of the Viz.AI Contact application, a clinical decision support software created to analyze CT results and notify providers of a potential stroke.

 

Recent Headlines

AI expert: Marriage of machine learning, radiology may turn out different than you think

Machine learning and artificial intelligence (AI) are two hotly discussed topics in healthcare, but radiologists tend to fear a future where computers replace people. But that fear may be unwarranted, according to one expert.

Lack of AI education in diagnostic radiology may be scaring off trainees

According to survey results recently published online in the Journal of the American College of Radiology, more than one-third of radiologists lack exposure to artificial intelligence (AI) educational material and resources. Additionally, most trainees' desire to learn about or pursue diagnostic radiology is hindered by AI's role in medicine.  

Deep learning CT model superior to state-of-the-art methods

A University of Saskatchewan team has created a deep learning technique that demonstrated enhanced de-noising capabilities in low-dose CT (LDCT) imaging, resulting in little resolution loss and better performance, according to a study published in the Journal of Digital Imaging.

Machine learning aids in detecting lung contour, reducing radiologist workload

Radiation therapy is an integral part of many cancer treatments. Ideally, doses are focused on the observable tumor while leaving surrounding organs unaffected, but determining the figuration of tumors and organs-at-risk is done manually—a time consuming and, at times, imprecise task for radiologists.

FDA grants 1st permission for AI stroke-detection imaging software

According to a Feb. 13 press release, the FDA announced clearance for the marketing of the Viz.AI Contact application, a clinical decision support software created to analyze CT results and notify providers of a potential stroke.

More hospitals than imaging centers are adopting AI, new report says

According to a December 2017 research survey conducted by the healthcare market research firm Reaction Data, most hospitals and imaging centers will be using machine learning or artificial intelligence (AI) technology by 2020.

AI and machine learning in radiology: 4 things to know

As industry experts continue to explore artificial intelligence (AI) applications in radiology, the question remains of whether AI applications can and will add value, including in new knowledge and information to provide patients with better outcomes at lower costs.

How accurate is machine learning in speech recognition? Researchers take a look

Artificial intelligence and machine learning are all the rage—and for good reason. But researchers claim the brain doesn’t actually use the regions identified by machine learning to perform a task. Rather, these algorithms reflect the mental associations related to the task.

MedyMatch Technology granted approval to fast-track AI software

MedyMatch Technology, a company dedicated to improving physician focused patient-assessments through artificial intelligence (AI) revealed it has been granted Expedited Access Pathway (EAP) designation by the United States Food and Drug Administration for intracranial hemorrhage detection software, according to a press release by the company.

Paul Chang: 3 things to know about AI, deep learning in 2018

As medical imaging continues to evolve, Health Imaging spoke with enterprise imaging and health informatics expert Paul Chang, MD, professor of radiology and vice chair rad informatics at the University of Chicago Medicine, about what practitioners and healthcare technology leaders should keep in mind regarding artificial intelligence (AI) and deep learning in the coming year.  

Pages