Search Results for author: Zeyu Gao

Found 13 papers, 4 papers with code

Personal Information Leakage Detection in Conversations

1 code implementation EMNLP 2020 Qiongkai Xu, Lizhen Qu, Zeyu Gao, Gholamreza Haffari

In this work, we propose to protect personal information by warning users of detected suspicious sentences generated by conversational assistants.

Language Modelling

Enhance Sample Efficiency and Robustness of End-to-end Urban Autonomous Driving via Semantic Masked World Model

no code implementations8 Oct 2022 Zeyu Gao, Yao Mu, Ruoyan Shen, Chen Chen, Yangang Ren, Jianyu Chen, Shengbo Eben Li, Ping Luo, YanFeng Lu

End-to-end autonomous driving provides a feasible way to automatically maximize overall driving system performance by directly mapping the raw pixels from a front-facing camera to control signals.

Autonomous Driving

Meta Mask Correction for Nuclei Segmentation in Histopathological Image

no code implementations24 Nov 2021 Jiangbo Shi, Chang Jia, Zeyu Gao, Tieliang Gong, Chunbao Wang, Chen Li

However, the development of such an automated method requires a large amount of data with precisely annotated masks which is hard to obtain.

Meta-Learning Nuclear Segmentation

PIMIP: An Open Source Platform for Pathology Information Management and Integration

no code implementations9 Nov 2021 Jialun Wu, Anyu Mao, Xinrui Bao, Haichuan Zhang, Zeyu Gao, Chunbao Wang, Tieliang Gong, Chen Li

However, there is still a lack of an open and universal digital pathology platform to assist doctors in the management and analysis of digital pathological sections, as well as the management and structured description of relevant patient information.

Management

BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network

no code implementations26 Oct 2021 Jialun Wu, Yang Liu, Zeyu Gao, Tieliang Gong, Chunbao Wang, Chen Li

To address this issue, we propose Biomedical Information Extraction, a hybrid neural network to extract relations from biomedical text and unstructured medical reports.

Knowledge Graphs Transfer Learning

A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning

no code implementations26 Oct 2021 Jialun Wu, Haichuan Zhang, Zeyu Gao, Xinrui Bao, Tieliang Gong, Chunbao Wang, Chen Li

Tumor region detection, subtype and grade classification are the fundamental diagnostic indicators for renal cell carcinoma (RCC) in whole-slide images (WSIs).

Classification whole slide images

W-Net: A Two-Stage Convolutional Network for Nucleus Detection in Histopathology Image

no code implementations26 Oct 2021 Anyu Mao, Jialun Wu, Xinrui Bao, Zeyu Gao, Tieliang Gong, Chen Li

In order to take advantage of segmentation methods based on point annotation, further alleviate the manual workload, and make cancer diagnosis more efficient and accurate, it is necessary to develop an automatic nucleus detection algorithm, which can automatically and efficiently locate the position of the nucleus in the pathological image and extract valuable information for pathologists.

A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data

no code implementations26 Oct 2021 Jialun Wu, Zeyu Gao, Haichuan Zhang, Ruonan Zhang, Tieliang Gong, Chunbao Wang, Chen Li

In this study, we propose a framework that combines pathological images and medical reports to generate a personalized diagnosis result for individual patient.

whole slide images

Renal Cell Carcinoma Detection and Subtyping with Minimal Point-Based Annotation in Whole-Slide Images

1 code implementation12 Aug 2020 Zeyu Gao, Pargorn Puttapirat, Jiangbo Shi, Chen Li

Semi-supervised learning (SSL) is an effective way to utilize unlabeled data and alleviate the need for labeled data.

whole slide images

OpenHI2 -- Open source histopathological image platform

no code implementations15 Jan 2020 Pargorn Puttapirat, Haichuan Zhang, Jingyi Deng, Yuxin Dong, Jiangbo Shi, Hongyu He, Zeyu Gao, Chunbao Wang, Xiangrong Zhang, Chen Li

Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine.

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