Clinical Edge Journal Scan

AI algorithm on par with radiologists as mammogram reader


 

Key clinical point : An artificial intelligence computer algorithm performed on par with, and in some cases exceeded, radiologists in reading mammograms from women undergoing routine screening.

Major finding : When operating at a specificity of 96.6%, the sensitivity was 81.9% for the algorithm, 77.4% for first-reader radiologists, and 80.1% for second-reader radiologists.

Study details : A comparison of algorithm and radiologist assessments of mammograms in 8,805 women, 739 of whom were diagnosed with breast cancer.

Disclosures: The research was funded by the Stockholm County Council. The investigators disclosed financial relationships with the Swedish Research Council, the Swedish Cancer Society, Stockholm City Council, Collective Minds Radiology, and Pfizer.

Source: Salim M et al. JAMA Oncol. 2020 Aug 27. doi: 10.1001/jamaoncol.2020.3321.

Recommended Reading

Pembrolizumab combo flops in pretreated HR-positive, ERBB2-negative breast cancer
MDedge Hematology and Oncology
First-in-class ADC ups survival in mTNBC
MDedge Hematology and Oncology
Abemaciclib cuts early recurrence in high-risk breast cancer
MDedge Hematology and Oncology
Global stomach cancer deaths decline as colorectal cancer deaths stagnate, rise
MDedge Hematology and Oncology
Divergent findings with paclitaxel and nab-paclitaxel in TNBC
MDedge Hematology and Oncology
Cancer disparities: One of the most pressing public health issues
MDedge Hematology and Oncology
The scope of under- and overtreatment in older adults with cancer
MDedge Hematology and Oncology
Radiotherapy planning scans reveal breast cancer patients’ CVD risk
MDedge Hematology and Oncology
Restarting breast cancer screening after disruption not so simple
MDedge Hematology and Oncology
NCI may ‘kill’ major mammography trial, says adviser
MDedge Hematology and Oncology