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Resources: Page 228
AI may enhance MRI-guided adaptive radiation therapy
By
Erik L. Ridley
Wednesday, November 29 | 3:00 p.m.-3:10 p.m. | SSM12-01 | Room S404CDArtificial intelligence (AI) can provide automatic contouring of tumors and organs to support daily MRI-guided adaptive radiation therapy, researchers will report in this Wednesday session.
November 5, 2017
Deep learning can predict infarction risk after stroke
By
Erik L. Ridley
Wednesday, November 29 | 11:00 a.m.-11:10 a.m. | SSK15-04 | Room N226In this morning talk, researchers will describe how deep learning can help guide treatment decisions for patients with acute ischemic stroke.
November 5, 2017
Pairing AI, radiologists improves bone age assessment
By
Erik L. Ridley
Wednesday, November 29 | 11:00 a.m.-11:10 a.m. | RC513-11 | Room E352In this scientific session, researchers will explain why artificial intelligence (AI) and radiologists are better together when it comes to bone age assessment.
November 5, 2017
CAD software tracks changes in brain metastases
By
Erik L. Ridley
Wednesday, November 29 | 11:00 a.m.-11:10 a.m. | RC505-09 | Room E451BComputer-aided detection (CAD) software can be used to detect and quantify changes in brain metastases on MRI, according to researchers from Philadelphia.
November 5, 2017
CADx software performs well for bone age assessment
By
Erik L. Ridley
Wednesday, November 29 | 10:50 a.m.-11:00 a.m. | RC513-10 | Room E352A computer-aided diagnosis (CADx) software application can accurately perform automated bone age assessment in children, a German group has found.
November 5, 2017
Machine learning can help predict KRAS mutation status
By
Erik L. Ridley
Wednesday, November 29 | 10:40 a.m.-10:50 a.m. | SSK07-02 | Room E353AMachine learning and quantitative MRI features can assist in predicting the KRAS mutation status of tumors in patients with metastatic colon cancer, according to Harvard researchers.
November 5, 2017
Finding breast cancer: How do computers compare with radiologists?
By
Kate Madden Yee
Wednesday, November 29 | 10:40 a.m.-10:50 a.m. | SSK02-02 | Room E451AHow do deep-learning algorithms compare with radiologists when it comes to finding cancer on mammography? Find out in this Wednesday morning presentation.
November 5, 2017
Deep-learning software boosts breast US performance
By
Kate Madden Yee
Tuesday, November 28 | 3:40 p.m.-3:50 p.m. | SSJ02-05 | Room E450AWhen it comes to identifying breast cancer, deep-learning software for breast ultrasound achieves diagnostic accuracy comparable to that of radiologists, Swiss researchers have found.
November 5, 2017
Machine learning predicts working memory performance
By
Erik L. Ridley
Tuesday, November 28 | 3:30 p.m.-3:40 p.m. | SSJ19-04 | Room N228This Tuesday afternoon session will reveal how machine learning can predict a person's working memory performance by analyzing brain white-matter microstructure.
November 5, 2017
Algorithm virtually enhances resolution of microdose CT
By
Abraham Kim
Tuesday, November 28 | 3:10 p.m.-3:20 p.m. | SSJ22-02 | Room S403BA major drawback of lowering CT radiation dose is a loss in image quality, but researchers found that microdose CT can deliver high-quality scans with the aid of a deep-learning algorithm.
November 5, 2017
Machine learning differentiates brain tumors
By
Erik L. Ridley
Tuesday, November 28 | 3:10 p.m.-3:20 p.m. | SSJ19-02 | Room N228Machine learning can distinguish between glioblastoma multiforme and primary central nervous system lymphoma on multiparametric MRI, according to researchers from Japan.
November 5, 2017
Deep learning can spot significant coronary stenosis
By
Erik L. Ridley
Tuesday, November 28 | 11:50 a.m.-12:00 p.m. | SSG02-09 | Room S504ABIn this session, researchers will describe how deep learning shows potential for identifying patients with functionally significant coronary artery stenosis.
November 5, 2017
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