Cargando…

Improving the Performance of Radiologists Using Artificial Intelligence-Based Detection Support Software for Mammography: A Multi-Reader Study

OBJECTIVE: To evaluate whether artificial intelligence (AI) for detecting breast cancer on mammography can improve the performance and time efficiency of radiologists reading mammograms. MATERIALS AND METHODS: A commercial deep learning-based software for mammography was validated using external dat...

Descripción completa

Detalles Bibliográficos
Autores principales:	Lee, Jeong Hoon, Kim, Ki Hwan, Lee, Eun Hye, Ahn, Jong Seok, Ryu, Jung Kyu, Park, Young Mi, Shin, Gi Won, Kim, Young Joong, Choi, Hye Young
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	The Korean Society of Radiology 2022
Materias:	Breast Imaging
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9081685/ https://www.ncbi.nlm.nih.gov/pubmed/35434976 http://dx.doi.org/10.3348/kjr.2021.0476

Ejemplares similares

The Efficacy of Mammography Boot Camp to Improve the Performance of Radiologists
por: Lee, Eun Hye, et al.
Publicado: (2014)

Deep Learning-Based Artificial Intelligence for Mammography
por: Yoon, Jung Hyun, et al.
Publicado: (2021)

Performance of Screening Mammography: A Report of the Alliance for Breast Cancer Screening in Korea
por: Lee, Eun Hye, et al.
Publicado: (2016)

Analysis of Participant Factors That Affect the Diagnostic Performance of Screening Mammography: A Report of the Alliance for Breast Cancer Screening in Korea
por: Kim, Young Joong, et al.
Publicado: (2017)

Use of Artificial Intelligence for Reducing Unnecessary Recalls at Screening Mammography: A Simulation Study
por: Kim, Yeon Soo, et al.
Publicado: (2022)

Validation of radiologists’ findings by computer-aided detection (CAD) software in breast cancer detection with automated 3D breast ultrasound: a concept study in implementation of artificial intelligence software
por: van Zelst, Jan CM, et al.
Publicado: (2019)

Effect of Different Types of Mammography Equipment on Screening Outcomes: A Report by the Alliance for Breast Cancer Screening in Korea
por: Choi, Bo Hwa, et al.
Publicado: (2019)

Interpretive Performance and Inter-Observer Agreement on Digital Mammography Test Sets
por: Kim, Sung Hun, et al.
Publicado: (2019)

Factors Affecting Breast Cancer Detectability on Digital Breast Tomosynthesis and Two-Dimensional Digital Mammography in Patients with Dense Breasts
por: Lee, Soo Hyun, et al.
Publicado: (2019)

A New Full-Field Digital Mammography System with and without the Use of an Advanced Post-Processing Algorithm: Comparison of Image Quality and Diagnostic Performance
por: Ahn, Hye Shin, et al.
Publicado: (2014)

Radiologists' Performance for Detecting Lesions and the Interobserver Variability of Automated Whole Breast Ultrasound
por: Kim, Sung Hun, et al.
Publicado: (2013)

Breast cancer detection: radiologists’ performance using mammography with and without automated whole-breast ultrasound
por: Kelly, Kevin M., et al.
Publicado: (2010)

Digital Breast Tomosynthesis versus MRI as an Adjunct to Full-Field Digital Mammography for Preoperative Evaluation of Breast Cancer according to Mammographic Density
por: Kim, Haejung, et al.
Publicado: (2022)

Can artificial intelligence reduce the interval cancer rate in mammography screening?
por: Lång, Kristina, et al.
Publicado: (2021)

Comparison of New and Established Full-Field Digital Mammography Systems in Diagnostic Performance
por: Ko, Eun Sook, et al.
Publicado: (2013)

The Value of Adding Ductography to Ultrasonography for the Evaluation of Pathologic Nipple Discharge in Women with Negative Mammography
por: Choi, Younjung, et al.
Publicado: (2022)

Contrast-Enhanced Spectral Mammography: Comparison with Conventional Mammography and Histopathology in 152 Women
por: Luczyńska, Elzbieta, et al.
Publicado: (2014)

Axillary Lymphadenopathy in the COVID-19 Era: What the Radiologist Needs to Know
por: Zhang, Meng, et al.
Publicado: (2022)

Introduction of a New Staging System of Breast Cancer for Radiologists: An Emphasis on the Prognostic Stage
por: Koh, Jieun, et al.
Publicado: (2019)

Survival Rates of Breast Cancer Patients Aged 40 to 49 Years according to Detection Modality in Korea: Screening Ultrasound versus Mammography
por: Won, So Yeon, et al.
Publicado: (2021)

Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study
por: van Winkel, Suzanne L., et al.
Publicado: (2021)

The Unusual Ultrasound Features of a Breast Cholesterol Granuloma Manifesting as an Intracystic Mass: Case Report and Literature Review
por: Ahn, Hye Shin, et al.
Publicado: (2013)

Metastatic melanoma presenting as a breast mass – role of radiologist as a clinician
por: Sharma, Swati, et al.
Publicado: (2020)

Tattoo pigment mimicking axillary lymph node calcifications on mammography
por: Paul Litton, Tyler, et al.
Publicado: (2020)

Syringomatous Adenoma of the Nipple on Screening Mammography: A Case Report
Publicado: (2021)

Detection of Contralateral Breast Cancer Using Diffusion-Weighted Magnetic Resonance Imaging in Women with Newly Diagnosed Breast Cancer: Comparison with Combined Mammography and Whole-Breast Ultrasound
por: Ha, Su Min, et al.
Publicado: (2021)

Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography
por: Choi, Ji Soo, et al.
Publicado: (2019)

Performance of Double Reading Mammography in an Iranian Population and Its Effect on Patient Outcome
por: Moradi, Maryam, et al.
Publicado: (2013)

Effects of delayed callback from screening mammography due to the COVID-19 pandemic
por: Chamadoira, Juliana, et al.
Publicado: (2023)

Digital Breast Tomosynthesis Plus Ultrasound Versus Digital Mammography Plus Ultrasound for Screening Breast Cancer in Women With Dense Breasts
por: Ha, Su Min, et al.
Publicado: (2023)

Bladder Cancer Metastasis to the Breast in a Male Patient: Imaging Findings on Mammography and Ultrasonography
Publicado: (2022)

Comparison of One- and Two-Region of Interest Strain Elastography Measurements in the Differential Diagnosis of Breast Masses
por: Park, Hee Jeong, et al.
Publicado: (2020)

Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts
por: van Zelst, Jan C. M., et al.
Publicado: (2018)

Sonoelastography in Distinguishing Benign from Malignant Complex Breast Mass and Making the Decision to Biopsy
por: Kim, Mi Young, et al.
Publicado: (2013)

Optimising breast cancer screening reading: blinding the second reader to the first reader’s decisions
por: Cooper, Jennifer A., et al.
Publicado: (2021)

Diagnostic Value of Contrast-Enhanced Spectral Mammography in Comparison to Magnetic Resonance Imaging in Breast Lesions
por: Xing, Dong, et al.
Publicado: (2019)

Contrast-Enhanced Spectral Mammography Versus Ultrasonography: Diagnostic Performance in Symptomatic Patients with Dense Breasts
por: Lu, Zhongfei, et al.
Publicado: (2020)

Patients characteristics related to screening mammography cancellation and rescheduling rates during the COVID-19 pandemic
por: Amornsiripanitch, Nita, et al.
Publicado: (2021)

Granular Cell Tumor Originating from the Pectoral Muscle: A Rare Extramammary Finding on Mammography
Publicado: (2022)

Experience of a single healthcare system with screening mammography before and after COVID-19 shutdown
por: Chesebro, Allyson L., et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_pnkjqs4csrupidmns0peoqur4t