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. 

RSS icon
Thumbnail

AI-powered triage software for mammograms gains FDA clearance

CureMetrix, a La Jolla, California-based healthcare technology company, has received FDA clearance for its new AI-based triage software solution for mammography.

Thumbnail

AI trained on more than 1M medical images accurately detects breast cancer

Researchers have developed a new convolutional neural network (CNN) that can predict the presence of breast cancer with the accuracy of an experienced radiologist. 

Thumbnail

Perfusion MRI shows CPAP healing the brains of apnea patients

It’s well established that widely used CPAP devices help give a good night’s rest to people with obstructive sleep apnea. Now an MRI-based study has shown the breathing assistance provided by continuous positive airway pressure also increases blood flow to, and blood volume in, the brain. 

Thumbnail

AI predicts how NSCLC patients will respond to chemotherapy

Artificial intelligence and radiomics can help specialists predict how patients with non–small cell lung cancer (NSCLC) will respond to chemotherapy, according to new research published in Radiology: Artificial Intelligence.

Thumbnail

Eye doctors using AI beat unassisted docs, AI alone at diagnosing diabetic vision loss

Google’s AI research group has shown that deep-learning algorithms can fine-tune ophthalmologists’ diagnosis of diabetic retinopathy on retinal fundus photographs, according to a study slated for publication in Ophthalmology. In the study, the physicians using the algorithm bested both AI alone and unassisted physicians on accuracy.

Thumbnail

Diattenuation imaging allows scientists to differentiate between brain tissues, types

Researchers can more accurately and comprehensively study the brain with a novel concept known as diattenuation imaging (DI)—a neuroimaging method that allows scientists to measure the polarization-dependent attenuation of light throughout different parts of the brain—according to a study published in Scientific Reports.

Thumbnail

Deep learning plus radiologist oversight boosts efficiency of liver lesion segmentation

When manually corrected by radiologists, an AI system for automatically detecting and segmenting colorectal metastases in the liver can improve interpretative efficiency, according to a study published online March 13 in Radiology: Artificial Intelligence.

Thumbnail

Imaging patients are concerned—but optimistic—about AI

Radiology patients are confident artificial intelligence will improve healthcare workflow and efficiency, but they’re skeptical of the tech itself and remain unsure of how AI will factor into the patient experience, according to a study published online March 14 in the Journal of the American College of Radiology.

Displaying 2585 - 2592 of 3119
Design by Adaptive Theme