Vail 2016: Computed Tomography in Clinical Practice

Jan 30th, 2016Feb 4th, 2016

Vail, CO

US

http://www.edusymp.com/product/details/838

Phone:800-338-5901

This symposium is structured to provide a comprehensive review of computed tomography. A balance of abdominal, cardiovascular, and central nervous system topics will be presented to help registrants expand their clinical practices.

PET/MRI reveals sex differences in patients with autism

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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.

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PET/MRI shows that young women with autism spectrum disorder have increased brain metabolism associated with translocator protein.

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Radiologist consultation improves patients' LCS attitudes

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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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Doctor Female Young Desk 400

Pisano speaks with AuntMinnie.com on new ARPA-H leadership role

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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

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

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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

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Deep-learning model determines breast tumor staging

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A deep-learning model based on mammographic images can determine tumor staging and sentinel lymph node metastasis in breast cancer patients.

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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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F-18 FDG and Ga-68 FAPI-46 images of a 51-year-old woman with adenocarcinoma with lepidic growth pattern in right upper lobe. (A) Maximum-intensity-projection PET images. The lesion had F-18 FDG uptake below blood pool level but was strongly Ga-68 FAPI-46-positive. CT-guided biopsy led to pathologic diagnosis of adenocarcinoma, and the patient was treated by stereotactic body radiation therapy because of functional inoperability. Image courtesy of the Journal of Nuclear Medicine.

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Can brain MRI for emergency imaging of dizziness be more effective?

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Predictors for acute conditions such as stroke could make brain MRI more effective in patients who present in the emergency department with dizziness or vertigo, according to recent research.

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