Artificial intelligence aims to improve breast cancer diagnoses

A recent study found that false positive breast biopsies cost the healthcare system over $2 billion per year. According to the National Cancer Institute, mammograms miss about 20% of breast cancers while one in 10 women receive a false positive result. Jamie Yuccas spoke with researchers at Google and UCLA who have developed an artificial intelligence program to help better diagnose mammograms and biopsies. Dr. Susan Grossman joins "CBS This Morning" to explain the need for the new technology.
Source: Health News: CBSNews.com - Category: Consumer Health News Source Type: news

Related Links:

Society categorizes patients based on risk associated with delaying services.
Source: Diagnostic Imaging - Category: Radiology Authors: Tags: Breast Cancer Infectious Diseases & Conditions/COVID-19 Mammography Source Type: news
BOSTON (CBS) — Julie Tolek remembers the exact minute her life changed forever: June 26, 2019. It was eight in the morning when she was diagnosed with breast cancer. “I thought I was in a dream. Nightmare, I guess, is a better description,” Tolek recalled. “I couldn’t say the word. It couldn’t be my life.” The diagnosis: stage two grade two invasive ductal carcinoma — an aggressively growing cancer. “I chose to have a double mastectomy even though my cancer was only in one breast. I decided I wanted to do everything in my power to not have to go through this again,&rdqu...
Source: WBZ-TV - Breaking News, Weather and Sports for Boston, Worcester and New Hampshire - Category: Consumer Health News Authors: Tags: Boston News Health Syndicated Local Breast Cancer Coronavirus Juli McDonald Mammograms Source Type: news
Lymphovascular invasion (LVI) has never been revealed by preoperative scans. It is necessary to use digital mammography in predicting LVI in patients with breast cancer preoperatively.
Source: BMC Cancer - Category: Cancer & Oncology Authors: Tags: Research article Source Type: research
AbstractObjectivesTo evaluate the usefulness of bilateral mammography in male patients with unilateral breast symptoms, including investigation of the diagnostic performance of unilateral and bilateral reviews and the average glandular dose (AGD) per exposure.MethodsTwo hundred seventy-one consecutive male patients (mean age, 57  years) with unilateral breast symptoms underwent bilateral mammography. Image interpretation was performed in two ways, first with a unilateral review of the symptomatic breast and then with a bilateral review. A modified BI-RADS scale (from 1 to 5) was used. The diagnostic performance of uni...
Source: European Radiology - Category: Radiology Source Type: research
Study shows three risk factors for breast cancer can be passed down through genes.
Source: Diagnostic Imaging - Category: Radiology Authors: Tags: Breast Cancer Cancer and Genetics Dense Breasts Mammography Source Type: news
The Research Letter titled “Evaluation of Triple-Negative Breast Cancer Early Detection Via Mammography Screening and Outcomes in African American and White American Patients,” published online February 19, 2020, included an error in the Methods section and another in the Results section. The Methods section notes the dat e of study termination as April 30, 2018. In fact, it was September 14, 2018. The Results section notes a median (range) follow-up time as 50.3 (1-36) months for African American patients; this should have been reported as 50.3 (1-91) months. Both errors have been corrected online.
Source: JAMA Surgery - Category: Sports Medicine Source Type: research
ConclusionsAccordingly, data mining approaches are proved to be a helpful tool to make the final decision as to whether patients should be referred to biopsy or not based on mammography reports. The developed CDSS may also be helpful especially for less experienced radiologists.
Source: Health Information Science and Systems - Category: Information Technology Source Type: research
We present a deep convolutional neural network for breast cancer screening exam classification, trained, and evaluated on over 200000 exams (over 1000000 images). Our network achieves an AUC of 0.895 in predicting the presence of cancer in the breast, when tested on the screening population. We attribute the high accuracy to a few technical advances. 1) Our network’s novel two-stage architecture and training procedure, which allows us to use a high-capacity patch-level network to learn from pixel-level labels alongside a network learning from macroscopic breast-level labels. 2) A custom ResNet-based network used as a...
Source: IEE Transactions on Medical Imaging - Category: Biomedical Engineering Source Type: research
Condition:   Breast Cancer Interventions:   Diagnostic Test: Serum Autotaxin;   Radiation: chest x-ray;   Diagnostic Test: Breast ultrasound or mammography;   Diagnostic Test: Histopathological examination of breast mass specimens;   Radiation: Magnetic Resonance Imaging ( MRI) and Bone scan;   Diagnostic Test: Peripheral  haemogram;   Diagnostic Test: Renal and liver functions;   Diagnostic Test: Prothrombin time and concentration;   Diagnostic Test: Cancer Antigen...
Source: ClinicalTrials.gov - Category: Research Source Type: clinical trials
Research reveals half of radiologists saw no change in their recall rates.
Source: Diagnostic Imaging - Category: Radiology Authors: Tags: Breast Cancer Breast Imaging Mammography Tomosynthesis Source Type: news
More News: Breast Cancer | Cancer | Cancer & Oncology | Health | Mammography | Study | Women