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3,675 results on '"Zhang, Yonghui"'

1. A comprehensive AI model development framework for consistent Gleason grading.

Author

Huo, Xinmi, Ong, Kok, Lau, Kah, Gole, Laurent, Young, David, Tan, Char, Zhu, Xiaohui, Zhang, Chongchong, Zhang, Yonghui, Li, Longjie, Han, Hao, Lu, Haoda, Zhang, Jing, Hou, Jun, Zhao, Huanfen, Gan, Hualei, Yin, Lijuan, Wang, Xingxing, Chen, Xiaoyue, Lv, Hong, Cao, Haotian, Yu, Xiaozhen, Shi, Yabin, Huang, Ziling, Marini, Gabriel, Xu, Jun, Liu, Bingxian, Chen, Bingxian, Wang, Qiang, Gui, Kun, Shi, Wenzhao, Sun, Yingying, Chen, Wanyuan, Cao, Dalong, Lee, Hwee, Hue, Susan, Yu, Weimiao, Tan, Soo, and Sanders, Stephan

Abstract

BACKGROUND: Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. METHODS: We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI. RESULTS: Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance. CONCLUSIONS: This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.

Published
2024

3. Discussion on the Practice of Narrative Medicine in Primary Care from the Perspective of General Practitioners

Author

WANG Lin, WANG Yixin, CHEN Tingyan, LIN Shaohai, ZHANG Yonghui

Subjects
general practice, narrative medicine, parallel medical records, primary health care, Medicine
Abstract

Primary health care provided by general practitioners is an important safeguard for the achievement of universal health coverage. With the continues progress of new medical reform, the number of primary care settings, general practitioners and outpatient visits have increased significantly compared with one decade ago. General practitioners, as the main body of implementation of general practice, coincides with the concept of narrative medicine in terms of patient-centeredness and attention to both psychological and social factors of the patients. Narrative medicine is medicine practiced by clinical workers who have narrative ability, with strong theory and weak practice in our country at present. From the perspective of general practitioners, this paper presents the positive influence of narrative medicine practice in primary care on general practitioners in the form of parallel medical records.

Published
2024
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4. Does Principal Component Analysis Preserve the Sparsity in Sparse Weak Factor Models?

Author

Wei, Jie and Zhang, Yonghui

Subjects
Economics - Econometrics
Abstract

This paper studies the principal component (PC) method-based estimation of weak factor models with sparse loadings. We uncover an intrinsic near-sparsity preservation property for the PC estimators of loadings, which comes from the approximately upper triangular (block) structure of the rotation matrix. It implies an asymmetric relationship among factors: the rotated loadings for a stronger factor can be contaminated by those from a weaker one, but the loadings for a weaker factor is almost free of the impact of those from a stronger one. More importantly, the finding implies that there is no need to use complicated penalties to sparsify the loading estimators. Instead, we adopt a simple screening method to recover the sparsity and construct estimators for various factor strengths. In addition, for sparse weak factor models, we provide a singular value thresholding-based approach to determine the number of factors and establish uniform convergence rates for PC estimators, which complement Bai and Ng (2023). The accuracy and efficiency of the proposed estimators are investigated via Monte Carlo simulations. The application to the FRED-QD dataset reveals the underlying factor strengths and loading sparsity as well as their dynamic features., Comment: 54 pages, 5 figures

Published
2023
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13. A One-Covariate-at-a-Time Method for Nonparametric Additive Models

Author

Su, Liangjun, Yang, Thomas Tao, Zhang, Yonghui, and Zhou, Qiankun

Subjects
Economics - Econometrics
Abstract

This paper proposes a one-covariate-at-a-time multiple testing (OCMT) approach to choose significant variables in high-dimensional nonparametric additive regression models. Similarly to Chudik, Kapetanios and Pesaran (2018), we consider the statistical significance of individual nonparametric additive components one at a time and take into account the multiple testing nature of the problem. One-stage and multiple-stage procedures are both considered. The former works well in terms of the true positive rate only if the marginal effects of all signals are strong enough; the latter helps to pick up hidden signals that have weak marginal effects. Simulations demonstrate the good finite sample performance of the proposed procedures. As an empirical application, we use the OCMT procedure on a dataset we extracted from the Longitudinal Survey on Rural Urban Migration in China. We find that our procedure works well in terms of the out-of-sample forecast root mean square errors, compared with competing methods.

Published
2022

22. Phosphoantigens glue butyrophilin 3A1 and 2A1 to activate Vγ9Vδ2 T cells

Author

Yuan, Linjie, Ma, Xianqiang, Yang, Yunyun, Qu, Yingying, Li, Xin, Zhu, Xiaoyu, Ma, Weiwei, Duan, Jianxin, Xue, Jing, Yang, Haoyu, Huang, Jian-Wen, Yi, Simin, Zhang, Mengting, Cai, Ningning, Zhang, Lin, Ding, Qingyang, Lai, Kecheng, Liu, Chang, Zhang, Lilan, Liu, Xinyi, Yao, Yirong, Zhou, Shuqi, Li, Xian, Shen, Panpan, Chang, Qing, Malwal, Satish R., He, Yuan, Li, Wenqi, Chen, Chunlai, Chen, Chun-Chi, Oldfield, Eric, Guo, Rey-Ting, and Zhang, Yonghui

Published
2023
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