Oncology | Pathology Histopathological Differential Diagnosis and Estrogen Receptor/Progesterone Receptor Immunohistochemical Evaluation of Breast Carcinoma Using a Deep Learning-Based Artificial Intelligence Architecture. September 6, 2024
Radiology Presurgical Upgrade Prediction of DCIS to Invasive Ductal Carcinoma Using Time-dependent Deep Learning Models with DCE MRI. June 20, 2024
Medical Imaging | Oncology | Pathology Enhancing histopathological image classification of invasive ductal carcinoma using hybrid harmonization techniques. November 16, 2023
Oncology | Pathology | Radiology End-to-end deep learning radiomics: development and validation of a novel attention-based aggregate convolutional neural network to distinguish breast diffuse large B-cell lymphoma from breast invasive ductal carcinoma. October 23, 2023
Radiology Multitask deep learning on mammography to predict extensive intraductal component in invasive breast cancer. October 9, 2023
Medical Imaging | Oncology | Pathology Performance analysis of seven Convolutional Neural Networks (CNNs) with transfer learning for Invasive Ductal Carcinoma (IDC) grading in breast histopathological images. November 10, 2022
Pathology The Use of Convolutional Neural Networks in the Prediction of Invasive Ductal Carcinoma in Histological Images of Breast Cancer. June 8, 2022
Oncology | Pathology Breast Invasive Ductal Carcinoma Classification on Whole Slide Images with Weakly-Supervised and Transfer Learning. November 13, 2021
Pathology Automated detection and grading of Invasive Ductal Carcinoma breast cancer using ensemble of deep learning models. October 19, 2021
Pathology Artificial intelligence in automatic classification of invasive ductal carcinoma breast cancer in digital pathology images. January 13, 2021
Radiology Visualizing “featureless” regions on mammograms classified as invasive ductal carcinomas by a deep learning algorithm: the promise of AI support in radiology. November 17, 2020
Oncology | Radiology Application of breast cancer diagnosis based on a combination of convolutional neural networks, ridge regression and linear discriminant analysis using invasive breast cancer images processed with autoencoders. November 24, 2019