Best of Oncology East

Nov 20th, 2014

Toronto, ON

CA

http://www.oncologyeducation.com/events/upcoming-events/best-of-oncology-east-2014/conference-home/

Phone:905-713-7171

Co-chaired by Dr. Robert El-Maraghi, Dr. Dorothy Lo, Dr. Sunil Verma, and Dr. Scott Berry, this meeting will highlight the top three to four most clinically relevant achievements of 2014 for nine different tumour sites

PET/MRI reveals sex differences in patients with autism

April 18, 2024

My BreastAI Suite by GE HealthCare

My BreastAI Suite by GE HealthCare

April 2, 2024

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

April 18, 2024

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.

AI proposed to help radiologists detect child abuse injuries

April 17, 2024

PET/MRI reveals sex differences in patients with autism

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

April 18, 2024

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.

April 18, 2024

Doctor Female Young Desk 400

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

By Amerigo Allegretto

Etta Pisano, MD, spoke with AuntMinnie.com on leading the Advancing Clinical Trials Readiness initiative, part of ARPA-H.

April 18, 2024

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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.

April 17, 2024

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

By Kate Madden Yee

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.

April 17, 2024

POCUS used widely in lung ultrasound applications

By Amerigo Allegretto

Some of the top domains for users of point-of-care ultrasound (POCUS) incorporate the technology for lung ultrasound applications.

April 17, 2024

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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.

April 16, 2024

ChatGPT-4 matches radiologists in flagging errors on reports

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.

April 16, 2024

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.

FAPI-PET shows promise in patients with lung cancer

FAPI-PET imaging could emerge as a new tool for assessing patients with single pulmonary tumors, especially in those with negative results on other scans.

April 15, 2024

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.

IMV: Nuclear medicine procedure volumes decrease

By Davin Korstjens

Total nuclear medicine patient study volumes decreased between 2021 and 2023, according to a newly published IMV 2024 Nuclear Medicine Market Outlook Report.

April 15, 2024

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

By Kate Madden Yee

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.

April 15, 2024

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