Erik L. Ridley[email protected]CTCan radiomics improve CT lung cancer screening?Two radiomics features on low-dose CT (LDCT) exams in lung cancer screening can be used to identify early-stage lung cancer patients who may be at higher risk for poor survival outcomes, potentially enabling earlier interventions, according to research published online June 29 in Scientific Reports.July 6, 2020AIACR, RSNA call on FDA to hold off on autonomous AIAutonomous artificial intelligence (AI) algorithms aren't close to being safe enough to replace radiologists, and the U.S. Food and Drug Administration (FDA) should hold off for now on developing regulatory pathways for autonomous AI in radiology, according to the American College of Radiology (ACR) and the RSNA.June 30, 2020CTAI algorithm can help in incidental detection of PEAn artificial intelligence (AI) algorithm can highlight incidental cases of pulmonary embolism (PE) on contrast-enhanced chest CT exams that were performed for reasons other than to detect PE, according to a presentation at the recent online annual conference of the Society for Imaging Informatics in Medicine.June 29, 2020Advanced VisualizationSIIM 2020: The future is now for 3D imagingThe future is now for 3D imaging technologies such as cinematic rendering, 3D printing, simulation training, virtual reality, and augmented reality, according to a June 26 presentation at the virtual annual meeting of the Society for Imaging Informatics in Medicine (SIIM).June 25, 2020AISIIM 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, 2020Previous PagePage 57 of 389Next PageTop StoriesCT'Habitat' AI model shows promise for stratifying lung nodule disease risk on LDCTThis type of model has an edge on its 2D and radiomics counterparts, researchers reported.MRICE MRI-based radiomics model captures DEB TACE-induced tumor changesUltrasoundPOCUS performs well in assessing pathologic venous congestionCTMachine learning plus CT helps assess severity of COPDUltrasoundActive thyroid surveillance effective, beneficial for older patients
