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Development and validation of a deep learning model for detection of breast cancers in mammography from multi-institutional datasets.

Daiju UedaAkira YamamotoNaoyoshi OnodaTsutomu TakashimaSatoru NodaShinichiro KashiwagiTamami MorisakiShinya FukumotoMasatsugu ShibaMina MorimuraTaro ShimonoKen KageyamaHiroyuki TatekawaKazuki MuraiTakashi HonjoAkitoshi ShimazakiDaijiro KabataYukio Miki
Published in: PloS one (2022)
The DL-based model developed for this study was able to detect all breast cancers with a very low mFPI. Our DL-based model achieved the highest performance to date, which might lead to improved diagnosis for breast cancer.
Keyphrases
  • deep learning
  • magnetic resonance imaging
  • magnetic resonance
  • young adults
  • artificial intelligence
  • loop mediated isothermal amplification
  • quantum dots
  • sensitive detection