A Study on the Performance of Generative Pre-trained Transformer (GPT) in Simulating Depressed Individuals on the Standardized Depressive Symptom Scale

no code implementations • 17 Jul 2023 • Sijin Cai, Nanfeng Zhang, Jiaying Zhu, Yanjie Liu, Yongjin Zhou

Compare GPT's responses with expected results, assess its understanding of depressive symptoms, and performance differences under different conditions.

Rethinking the optimization process for self-supervised model-driven MRI reconstruction

no code implementations • 18 Mar 2022 • Weijian Huang, Cheng Li, Wenxin Fan, Yongjin Zhou, Qiegen Liu, Hairong Zheng, Shanshan Wang

Recovering high-quality images from undersampled measurements is critical for accelerated MRI reconstruction.

MRI Reconstruction Self-Supervised Learning

D-UNet: a dimension-fusion U shape network for chronic stroke lesion segmentation

2 code implementations • 14 Aug 2019 • Yongjin Zhou, Weijian Huang, Pei Dong, Yong Xia, Shan-Shan Wang

This function adds a weighted focal coefficient and combines two traditional loss functions.

Image Segmentation Lesion Segmentation +2

Classifying Mammographic Breast Density by Residual Learning

no code implementations • 21 Sep 2018 • Jingxu Xu, Cheng Li, Yongjin Zhou, Lisha Mou, Hairong Zheng, Shan-Shan Wang

Mammographic breast density, a parameter used to describe the proportion of breast tissue fibrosis, is widely adopted as an evaluation characteristic of the likelihood of breast cancer incidence.

Classification General Classification