Background There is considerable interest in the potential use of artificial intelligence (AI)
systems in mammographic screening. However, it is essential to critically evaluate the …

Please see the Editorial Comment by Sadia Khanani discussing this article. Artificial
intelligence (AI) applications for screening mammography are being marketed for clinical …

With the help of machine learning, many of the problems that have plagued mammography
in the past have been solved. Effective prediction models need many normal and tumor …

Several studies have demonstrated the value of artificial intelligence (AI) applications in
breast cancer diagnosis. The systematic review of AI applications in breast cancer diagnosis …

Background The Personal Performance in Mammographic Screening (PERFORMS) scheme
is used to assess reader performance. Whether this scheme can assess the performance of …

High-grade serous ovarian cancer is the most lethal gynaecological malignancy. Detailed
molecular studies have revealed marked intra-patient heterogeneity at the tumour …

Background Breast screening enables early detection of cancers; however, most women
have normal mammograms, resulting in repetitive and resource-intensive reading tasks …

Deep learning algorithms are designed to learn from the data, where these require large
amount of training dataset for accurate prediction. Recent studies have depicted that transfer …

Accumulating evidence from retrospective studies demonstrate at least non-inferior
performance when using AI algorithms with different strategies versus double-reading in …

Background Double reading can be used in screening mammography, but it is labor
intensive. There is limited evidence on whether trained radiographers (ie, technologists) …