Erik L. Ridley[email protected]ISCTA studies in the ED add to burden for radiologistsSunday, December 1 | 11:25 a.m.-11:35 a.m. | SSA06-05 | Room N227BA team of researchers will share data quantifying the increase in radiologist workload from CT angiography (CTA) exams for evaluating aortic pathologies in the emergency department (ED).November 13, 2019ISStructured reporting improves endometriosis evaluationSunday, December 1 | 10:55 a.m.-11:05 a.m. | SSA10-02 | Room N228Researchers from Massachusetts will describe how the combination of structured reporting and reader expertise can improve the diagnosis and staging of endometriosis on MRI.November 13, 2019Digital X-RayDeep-learning algorithm bolsters lung cancer detectionRadiologists using a deep-learning algorithm can detect more cases of lung cancer on chest radiographs than they could without help from the software, while also having fewer false positives, according to research published online November 12 in Radiology.November 11, 2019AIStudy: Public image datasets may have QC issuesTwo large public image datasets commonly used to train artificial intelligence algorithms have quality control (QC) issues that could potentially limit their utility, according to research published online November 6 in Academic Radiology.November 10, 2019CTAI algorithm could enhance CT lung cancer screeningTuesday, December 3 | 3:50 p.m.-4:00 p.m. | SSJ05-06 | Room S102CDAn artificial intelligence (AI) algorithm could help radiologists improve their diagnostic accuracy on CT lung cancer screening exams, according to this presentation.November 6, 2019AIAI needs robust clinical evaluation in healthcareIt's not enough for a healthcare artificial intelligence (AI) algorithm to be highly accurate. To be widely adopted in clinical use, it must demonstrate improvement in quality of care and patient outcomes, according to an opinion article published online October 29 in BMC Medicine.November 5, 2019AIGANs ease 'big data' problem in training AI algorithmsMonday, December 2 | 11:40 a.m.-11:50 a.m. | SSC04-08 | Room S102CDA type of AI technology called generative adversarial networks (GANs) that was trained using normal brain CT scans is able to detect various intracranial diseases, according to a study by researchers from South Korea.November 3, 2019CTAI algorithm could enhance CT lung cancer screeningTuesday, December 3 | 3:50 p.m.-4:00 p.m. | SSJ05-06 | Room S102CDAn artificial intelligence (AI) algorithm could help radiologists improve their diagnostic accuracy on CT lung cancer screening exams, according to this presentation.November 3, 2019MRIAI classifies IDH mutation status in brain tumorsThursday, December 5 | 11:30 a.m.-11:40 a.m. | SSQ15-07 | Room S404ABAn artificial intelligence (AI) algorithm was able to classify the mutation status of isocitrate dehydrogenase (IDH) in brain tumors in a study by researchers from Texas.November 3, 2019UltrasoundDeep-learning model could triage renal ultrasound examsThursday, December 5 | 11:10 a.m.-11:20 a.m. | SSQ10-05 | Room E352A deep-learning algorithm can detect abnormalities on renal ultrasound exams, potentially enabling triage of these cases for radiologists, according to this scientific presentation.November 3, 2019Previous PagePage 69 of 389Next PageTop StoriesCTMachine learning plus CT helps assess severity of COPDA machine-learning model based on chest CT images accurately predicts lung function, which can help clinicians diagnose and assess COPD.UltrasoundActive thyroid surveillance effective, beneficial for older patientsMolecular ImagingFES-PET shows promise staging women with invasive lobular cancerCTStructured CT reporting tool may aid hernia detection after bariatric surgeryMRIHigher ventricular and atrial heart volumes boost cardiac disease risk
