Xiaoqin Wang

LIANG: IMPROVED TRAINABLE CALIBRATION METHOD FOR NEURAL NETWORKS 1 Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification1

Nathan Jacobs, G. Liang, Yu Zhang, 2020 .

Classification of Whole Mammogram and Tomosynthesis Images Using Deep Convolutional Neural Networks

Xiaoqin Wang, Jinze Liu, Xiaofei Zhang, 2018, IEEE Transactions on NanoBioscience.

Inconsistent Performance of Deep Learning Models on Mammogram Classification.

Hunter Blanton, Yu Zhang, Xiaoqin Wang, 2020, Journal of the American College of Radiology : JACR.

Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification pdf

Xiaoqin Wang, Gongbo Liang, Nathan Jacobs, 2020, ArXiv.

Whole mammogram image classification with convolutional neural networks

Xiaoqin Wang, Yi Zhang, Nathan Jacobs, 2017, 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Weakly-Supervised Self-Training for Breast Cancer Localization*

Yu Zhang, Xiaoqin Wang, Gongbo Liang, 2020, 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Contrastive Cross-Modal Pre-Training: A General Strategy for Small Sample Medical Imaging

Nathan Jacobs, Ramakanth Kavuluru, G. Liang, 2020, IEEE Journal of Biomedical and Health Informatics.

Weakly-Supervised Feature Learning via Text and Image Matching pdf

Connor Greenwell, Yu Zhang, Xiaoqin Wang, 2020, ArXiv.

Joint 2D-3D Breast Cancer Classification

Hunter Blanton, Yu Zhang, Xiaoqin Wang, 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

Transfer deep learning mammography diagnostic model from public datasets to clinical practice: a comparison of model performance and mammography datasets

Xiaoqin Wang, Quan Chen, Xiaofei Zhang, 2018, Other Conferences.