Improving mammography interpretation for both novice and experienced readers: a comparative study of two commercial artificial intelligence software-Reference-Cited by-同舟云学术

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Improving mammography interpretation for both novice and experienced readers: a comparative study of two commercial artificial intelligence software

Published:2023-11-08 Issue: Volume: Page:
ISSN:1432-1084
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Kim Hee Jeong,Choi Woo Jung^ORCID,Gwon Hye Yun,Jang Seo Jin,Chae Eun Young,Shin Hee Jung,Cha Joo Hee,Kim Hak Hee

Publisher

Springer Science and Business Media LLC

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s00330-023-10422-8.pdf

Reference40 articles.

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2. Mook S, Van ’t Veer LJ, Rutgers EJ et al (2011) Independent prognostic value of screen detection in invasive breast cancer. J Natl Cancer Inst 103:585–597

3. Lehtimäki T, Lundin M, Linder N et al (2011) Long-term prognosis of breast cancer detected by mammography screening or other methods. Breast Cancer Res 13:R134

4. Siu AL (2016) Screening for breast cancer: U.S. Preventive Services Task Force Recommendation Statement. Ann Intern Med 164:279–296

5. Cardoso F, Kyriakides S, Ohno S et al (2019) Early breast cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up†. Ann Oncol 30:1194–1220

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1. KI-gestützte Auswertung von Mammografieaufnahmen;Senologie - Zeitschrift für Mammadiagnostik und -therapie;2024-09

2. MAMMA – KI-gestützte Auswertung von Mammografieaufnahmen;RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren;2024-05-22

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