Erik L. Ridley[email protected]BreastIn-house data train breast cancer detection algorithmWednesday, November 28 | 11:20 a.m.-11:30 a.m. | SSK02-06 | Room E451BResearchers from California will share how deep-learning algorithms for breast cancer detection can be trained using an in-house image database.October 29, 2018BreastDeep learning may yield sharply lower dose from DBTMonday, November 26 | 3:00 p.m.-3:10 p.m. | SSE23-01 | Room S502ABIn this scientific session, a multi-institutional team of researchers will share how deep-learning technology could lead to nearly 80% lower radiation dose to patients from digital breast tomosynthesis (DBT) studies.October 29, 2018BreastAI speeds up DBT reading time, helps find more cancersMonday, November 26 | 11:20 a.m.-11:30 a.m. | RC215-14 | Arie Crown TheaterIn this talk, researchers will report that the concurrent use of artificial intelligence (AI) software while interpreting digital breast tomosynthesis (DBT) screening exams leads to higher radiologist accuracy and much faster reading times.October 29, 2018BreastDeep learning elevates mammography CAD performanceMonday, November 26 | 11:10 a.m.-11:20 a.m. | RC215-13 | Arie Crown TheaterMammography computer-aided detection (CAD) software based on deep learning can perform comparably to radiologists in detecting breast cancer and at a higher level than traditional mammography CAD applications, according to Dutch researchers.October 29, 2018AIRoad to RSNA 2018: Artificial Intelligence PreviewWelcome to the first installment of this year's Road to RSNA preview of the RSNA 2018 meeting in Chicago. For the 10th year in a row, we're providing a modality-by-modality overview of selected scientific presentations to serve as your guide to events at McCormick Place. Our journey along the Road to RSNA begins with our preview of artificial intelligence (AI). Researchers will travel to the Windy City to share their experiences working with and developing AI applications in all aspects of the imaging process.October 28, 2018CTAI algorithm can triage routine abdominal CT examsThursday, November 29 | 10:20 a.m.-10:30 a.m. | RC608-07 | Room E451BA Swiss team will describe how an artificial intelligence (AI) algorithm can identify acute findings on routine abdominal CT scans, enabling radiologists to prioritize reading of these urgent exams.October 28, 2018AIAlgorithm accurately detects changes on chest x-raysWednesday, November 28 | 11:40 a.m.-11:50 a.m. | SSK05-08 | Room N227BIn this talk, researchers will report that a machine-learning algorithm can perform better than radiologists in detecting changes in findings on serial chest radiographs.October 28, 2018AIDeep learning bolsters interpretation of chest x-raysWednesday, November 28 | 11:20 a.m.-11:30 a.m. | SSK05-06 | Room N227BResearchers from South Korea will present their deep-learning algorithm for the automatic detection of major thoracic abnormalities on chest radiographs.October 28, 2018BreastAI-based CAD can improve breast cancer detectionWednesday, November 28 | 11:30 a.m.-11:40 a.m. | SSK02-07 | Room E451BComputer-aided detection (CAD) software based on artificial intelligence (AI) can increase radiologist breast cancer detection rates, according to this scientific presentation.October 28, 2018BreastIn-house data train breast cancer detection algorithmWednesday, November 28 | 11:20 a.m.-11:30 a.m. | SSK02-06 | Room E451BResearchers from California will share how deep-learning algorithms for breast cancer detection can be trained using an in-house image database.October 28, 2018Previous PagePage 91 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
