American Association of Physicists in Medicine (AAPM) Annual Meeting

Jul 11th, 2020Jul 15th, 2020
Vancouver, BC
CA
https://www.aapm.org
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MR elastography effective for assessing liver stiffness in children
By Kate Madden Yee
MR elastography is an effective technique for noninvasive monitoring of liver stiffness -- a surrogate for fibrosis -- in children and young adults with autoimmune liver disease, researchers have reported.
April 19, 2024
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High breast density tied to impaired recurrence-free cancer survival
By Amerigo Allegretto
Recurrence-free breast cancer survival is less likely in women with high breast density compared with women with low density.
April 19, 2024
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Can ChatGPT ‘data mine’ patient reports for stroke registries?
By Will Morton
ChatGPT-4 appears useful for extracting details from reports on thrombectomy procedures in stroke patients, a labor-intensive and error-prone task currently performed by human readers.
April 19, 2024
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PET/MRI reveals sex differences in patients with autism
By Will Morton
PET/MRI shows that young women with autism spectrum disorder have increased brain metabolism associated with translocator protein.
April 18, 2024
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Radiologist consultation improves patients' LCS attitudes
By Kate Madden Yee
Consulting with a radiologist boosts patients' attitudes toward lung cancer screening (LCS) and their interest in quitting smoking, researchers have reported.
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Etta Pisano, MD, spoke with AuntMinnie.com on leading the Advancing Clinical Trials Readiness initiative, part of ARPA-H.
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AI proposed to help radiologists detect child abuse injuries
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A team at Michigan State University has developed an AI model designed to detect rib fractures in children under 3 years old.
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Test set images with ground truth (teal, red) and model predictions (green, yellow), with true positives (green), false positives (yellow), and false negatives (red). Predictions from the 6x-YOLOv5 ensemble trained on histogram equalized input images with a y = 0.2 avalanche scheme, achieving 0.536 precision, 0.795 recall, and 0.723 F2 score. Image and caption courtesy of Scientific Reports.
Tailored lung cancer screening model helps determine nodule follow-up
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A personalized lung cancer screening model used with patients with pulmonary nodules identified on low-dose CT helps clinicians determine how to follow up better than rule-based protocols, researchers have found.
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POCUS used widely in lung ultrasound applications
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Some of the top domains for users of point-of-care ultrasound (POCUS) incorporate the technology for lung ultrasound applications.
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CT-based deep learning identifies patients at further lung cancer risk
By Kate Madden Yee
A CT-based deep learning model can identify individuals with clinical stage IA non-small cell lung cancer (NSCLC) at high risk of further disease, researchers have found.
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ChatGPT-4 matches radiologists in flagging errors on reports
By Will Morton
ChatGPT-4 matched radiologists when tasked with detecting errors in imaging reports, with the study suggesting the technology may be useful for improving reporting accuracy.
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Deep-learning model determines breast tumor staging
By Amerigo Allegretto
A deep-learning model based on mammographic images can determine tumor staging and sentinel lymph node metastasis in breast cancer patients.
April 16, 2024
Researchers explain the data preparation and structure of a proposed CNN-based deep learning model using mammography features to determine breast tumor staging. The image is available for use under a Creative Commons license: CC BY-NC-ND 4.0 DEED Attribution-NonCommercial-NoDerivs 4.0 International.
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