N
Nehmat Houssami
Researcher at University of Sydney
Publications - 315
Citations - 18809
Nehmat Houssami is an academic researcher from University of Sydney. The author has contributed to research in topics: Breast cancer & Mammography. The author has an hindex of 65, co-authored 284 publications receiving 15857 citations. Previous affiliations of Nehmat Houssami include Westmead Hospital & Royal Hospital for Women.
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Incremental effect from integrating 3D-mammography (tomosynthesis) with 2D-mammography: Increased breast cancer detection evident for screening centres in a population-based trial
Francesca Caumo,Daniela Bernardi,Stefano Ciatto,Petra Macaskill,Marco Pellegrini,Silvia Brunelli,Paola Tuttobene,Paola Bricolo,Carmine Fantò,Marvi Valentini,Stefania Montemezzi,Nehmat Houssami +11 more
TL;DR: Integrated 2D/3D-mammography significantly increased cancer detection for both screening services; potential reduction in FPR is likely to differ between centres with those experiencing relatively higher FPR most likely to benefit from 2D/(3D)/3D mammography screening.
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Overdiagnosis of breast cancer in population screening: does it make breast screening worthless?
TL;DR: Future efforts should be directed towards ensuring that any changes in the implementation of BC screening optimize the balance between benefit and harms, and informing women of all the outcomes that may affect them when they participate in screening using well-crafted and balanced information.
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The prevention, detection, and management of breast cancer
TL;DR: Neoadjuvant endocrine therapy is an underutilised treatment in postmenopausal women with oestrogen‐receptor‐positive large operable or locally advanced cancers, and makes more patients suitable for surgery and offers others the choice of breast conservation.
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Evidence relevant to the investigation of breast symptoms: the triple test
TL;DR: Measures of test accuracy for the components of the triple test that allow easy estimation of the probability of breast cancer in symptomatic women, given any possible combination of results are presented.
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Early detection of breast cancer: overview of the evidence on computer-aided detection in mammography screening.
TL;DR: Refinement in CAD algorithms, in combination with increasing implementation of digital mammography, may improve the potential use of CAD in mammography reading, but will require prospective evaluation.