Erik L. Ridley[email protected]AISIIM 2020: Human element shouldn't be neglected with AISure, artificial intelligence (AI) in radiology is cool. But it's not enough to show results in a lab; the technology's real-world impact on efficacy and efficiency also needs to be evaluated, according to a June 25 talk at the virtual annual meeting of the Society for Imaging Informatics in Medicine (SIIM).June 24, 2020AISIIM 2020: How to create robust radiology AI algorithmsIt's not easy to develop radiology artificial intelligence (AI) algorithms that don't just perform well on data that are similar to what they are trained on. But there are ways to help improve AI robustness, according to June 24 talks at the virtual annual meeting of the Society for Imaging Informatics in Medicine (SIIM).June 24, 2020MRI4D Flow MRI is feasible during exerciseCardiac 4D flow MRI can quantify blood flow in the ascending aorta and main pulmonary artery during strenuous exercise, offering potential as a useful modality for evaluating right-sided heart dysfunction, according to research published online June 18 in Radiology: Cardiothoracic Imaging.June 18, 2020AI5 ways rads can use social media to shift AI narrativeMisleading commentary and incorrect information on social media regarding the impact of artificial intelligence (AI) on radiology can significantly impact how the specialty is perceived, and it's time for radiologists to reshape the conversation, according to an article published online June 15 in Clinical Imaging.June 18, 2020CTAI algorithm detects appendicitis on CT exams in ERSouth Korean researchers developed an artificial intelligence (AI) algorithm that was highly accurate and generalizable for detecting acute appendicitis on CT exams in emergency room (ER) patients. The algorithm could, if necessary, potentially fill in for a radiologist, according to research published online June 12 in Scientific Reports.June 17, 2020AIAuntMinnie.com Artificial Intelligence InsiderJune 15, 2020Image-Guided SurgeryAugmented reality supports liver tumor ablationAugmented reality technology shows potential for improving the speed and safety of liver tumor ablation procedures, according to research presented during a virtual session of the Society of Interventional Radiology's annual scientific meeting.June 15, 2020MRIDeep learning detects HCC on contrast-enhanced MRIA deep-learning algorithm can detect hepatocellular carcinoma (HCC) on contrast-enhanced liver MRI exams within seconds and at an accuracy level comparable to a less-experienced radiologist, according to a preliminary study published online June 11 in Scientific Reports.June 11, 2020Image ProcessingMuscle metrics on chest CT can predict mortality riskMeasurements of muscle mass and density automatically extracted from chest CT exams using an artificial intelligence (AI)-based model can predict all-cause mortality over a six-year period in older men, according to research published online June 6 in the Journals of Gerontology.June 11, 2020AIGender imbalance in AI training datasets lowers resultsArtificial intelligence (AI) algorithms trained with more cases from one gender can yield biased computer-aided diagnosis applications that perform worse on imaging exams involving the other gender, according to research published online May 26 in the Proceedings of the National Academy of Sciences.June 8, 2020Previous PagePage 58 of 389Next PageTop StoriesAIU.S. FDA may need to clarify SaMD validation standardsIn a video interview, a Dana-Farber Cancer Institute expert describes what the "rigor spectrum" is in validation study designs.Molecular ImagingPSMA-PET/CT may replace NaF-PET/CT in advanced prostate cancerWomens ImagingPreop breast MRI improves surgical planning, but use disparities remainWomens ImagingFIGO classification from MRI leads to moderate agreement among radsSponsor ContentRegister Now: Breaking Barriers in Breast Imaging Webinar
