Research Presentation Session

Artificial intelligence and machine learning in breast

Lectures

1
RPS 702 - Leveraging ipsilateral dual-view information for mass detection in mammograms using deep learning

RPS 702 - Leveraging ipsilateral dual-view information for mass detection in mammograms using deep learning

03:41Ma Jie, Shenzhen / China

2
RPS 702 - Artificial intelligence-based breast density classifier improves mammography reporting reliability

RPS 702 - Artificial intelligence-based breast density classifier improves mammography reporting reliability

04:52A. Watanabe, Manhattan beach, CA / United States

3
RPS 702 - MRI-based radiomics for prediction to neoadjuvant chemotherapy in breast cancer: a referral centre analysis

RPS 702 - MRI-based radiomics for prediction to neoadjuvant chemotherapy in breast cancer: a referral centre analysis

04:56F. Pesapane, Milan / Italy

4
RPS 702 - Measuring short and long-term breast cancer risk by combining mammographic texture models, an AI-based CAD system, and established risk factors

RPS 702 - Measuring short and long-term breast cancer risk by combining mammographic texture models, an AI-based CAD system, and established risk factors

04:59A. Lauritzen, Copenhagen / Denmark

5
RPS 702 - Evaluation of 3T multiparametric MRI with radiomic analysis for differentiating benign and malignant breast lesions

RPS 702 - Evaluation of 3T multiparametric MRI with radiomic analysis for differentiating benign and malignant breast lesions

04:42A. Vamvakas, Larissa / Greece

6
RPS 702 - Diagnostic performance of AI for cancers registered in a mammography screening program: a retrospective analysis

RPS 702 - Diagnostic performance of AI for cancers registered in a mammography screening program: a retrospective analysis

04:34Y. Köylüoğlu, Istanbul / Turkey

7
RPS 702 - Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer based on the integration of tumour heterogeneity and angiogenesis properties at MRI

RPS 702 - Radiomic machine learning for predicting prognostic biomarkers and molecular subtypes of breast cancer based on the integration of tumour heterogeneity and angiogenesis properties at MRI

06:24H. Park, Ansan / Korea, Republic of

8
RPS 702 - Radiomics analysis in breast MRI for non-invasive (in situ) breast cancer characterisation: initial results

RPS 702 - Radiomics analysis in breast MRI for non-invasive (in situ) breast cancer characterisation: initial results

03:42G. Lavazza, Turin / Italy

9
RPS 702 - Machine learning approaches for optimization in MRI texture analysis of breast cancer to predict prognostic biomarkers and molecular subtypes

RPS 702 - Machine learning approaches for optimization in MRI texture analysis of breast cancer to predict prognostic biomarkers and molecular subtypes

05:05H. Park, Ansan / Korea, Republic of

10
RPS 702 - DCE-MRI radiomics analysis for breast lesions characterisation

RPS 702 - DCE-MRI radiomics analysis for breast lesions characterisation

05:37M. Di Marco, Palermo / Italy

11
RPS 702 - Using AI to identify normal cases that may not need a second reader assessment in a French breast cancer screening program (BCSP): a retrospective evaluation

RPS 702 - Using AI to identify normal cases that may not need a second reader assessment in a French breast cancer screening program (BCSP): a retrospective evaluation

05:51H. Jarraya, Arras / France

12
RPS 702 - Comparison of artificial intelligence/machine learning algorithm in reporting computed radiography (CR) and digital radiography (DR) mammography studies

RPS 702 - Comparison of artificial intelligence/machine learning algorithm in reporting computed radiography (CR) and digital radiography (DR) mammography studies

04:42R. Ananthasivan, Bangalore / India

13
RPS 702 - Mammographic breast density assessment via deeply aggregating bilateral context information

RPS 702 - Mammographic breast density assessment via deeply aggregating bilateral context information

04:35Ma Jie, Shenzhen / China