Erik L. Ridley[email protected]Digital X-RayAI improves lung cancer detection on x-raysAn artificial intelligence (AI) algorithm can catch lung cancers that were initially missed by radiologists on chest radiographs and improve radiologist performance when used as a second reader, according to research published online December 10 in Radiology: Cardiothoracic Imaging.December 10, 2020Advanced VisualizationAI body analysis finds lung cancer survival risk factorsAn artificial intelligence (AI) algorithm was able to quickly analyze body composition metrics on abdominal/pelvic CT exams, yielding better prognostic information for survival in lung cancer patients than a patient's body mass index, according to research presented at the virtual RSNA 2020 meeting.December 10, 2020PACS/VNASecurity advisories issued for GE imaging systemsA security vulnerability found in more than 100 imaging systems from GE Healthcare could enable a cyberattacker to access or modify patient data, according to GE, security firm CyberMDX, and the U.S. Department of Homeland Security's Industrial Control Systems Cyber Emergency Response Team.December 7, 2020Advanced VisualizationMRI radiomics predicts axillary lymph node metastasisIn patients with early-stage breast cancer, "signatures" derived from MRI radiomics and patient clinical risk characteristics can be utilized to preoperatively predict axillary lymph node metastasis as well as disease-free survival, according to research published online December 8 in JAMA Network Open.December 7, 2020Advanced VisualizationCT radiomics characterizes complex cystic renal lesionsA machine-learning algorithm based on CT radiomics analysis can enable better preoperative risk classification of complex cystic renal lesions than relying only on the traditional Bosniak classification criteria, according to an international multicenter study presented Friday at the virtual RSNA 2020 meeting.December 6, 2020MRIFederated learning may boost AI generalizabilityTraining deep-learning algorithms with a federated-learning approach could help address the challenge of improving the performance of radiology artificial intelligence (AI) software across institutions, according to a presentation in a scientific session at this week's virtual RSNA 2020 meeting.December 2, 2020CTDeep-learning algorithm detects free air on CT imagesA deep-learning algorithm was able to detect and quantify regions of free air on CT images, enabling patients with these critical pathologies to be prioritized on the radiology worklist, according to a presentation on Wednesday morning at the virtual RSNA 2020 meeting.December 2, 2020CTAI abdominal fat analysis assesses cardiovascular riskBody composition metrics automatically calculated from abdominal CT exams by an artificial intelligence (AI) algorithm are significantly associated with patient risk for future major cardiovascular events, according to a Wednesday morning presentation at the RSNA 2020 virtual meeting.December 1, 2020CTMachine-learning model predicts adverse cardiac outcomesA machine-learning algorithm for analysis of coronary CT angiography exams was able to predict major adverse cardiac events at a higher level of accuracy than other traditional risk scores and risk factors, according to a presentation on Tuesday morning at the virtual RSNA 2020 meeting.November 30, 2020BreastCan AI be a second reader in breast cancer screening?An artificial intelligence (AI) algorithm could obviate the need for a second radiologist to review a screening mammogram in more than four out of five exams performed for a national breast cancer screening program, according to a presentation on Monday morning at the virtual RSNA 2020 meeting.November 29, 2020Previous PagePage 48 of 388Next PageTop StoriesMolecular ImagingVisual reads of amyloid PET scans effective in real-world settingsThe findings support the use of amyloid PET scans as acquired and visually read in the real world.MRIMRI reveals effects of ultraprocessed food on the heartPractice ManagementASRT survey shows vacancy rates still high among imaging departmentsDigital X-RayCan eye gaze data from radiologists make AI more human?Sponsor ContentWhen CT meets the power of AI everyone benefits.
