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Articles by Shaobin Chen
Uncertainty-inspired open-set model for identifying infantile fundus abnormalities
Abstract Accurate and safe identification of infantile fundus abnormalities is critical for large-scale screening, yet remains challenging because of heterogeneous disease presentations and overconfident predictions by conventional artificial intelligence (AI) models. In this study, we aim to develop an uncertainty-inspired open-set (UIOS) system to address these challenges.
ROP-VL: An Open Dataset Integrating Fundus Photograph and Clinical Knowledge for Retinopathy of Prematurity
Abstract The development of advanced artificial intelligence (AI) for Retinopathy of Prematurity (ROP) is hindered by a scarcity of public datasets that integrate color fundus photographs with the expert clinical knowledge required for building robust vision-language models. We present ROP-VL, an open-access dataset designed to bridge this critical gap.
Algorithmic Trading Regulation and Stock Market Liquidity: Evidence from China’s A-Share Market
You are already at the latest version We examine how restricting high-frequency trading (HFT) affects stock liquidity in China’s A-share market. Using China’s 2024 Provisions on Program Trading in the Securities Market as a quasi-natural experiment, we construct a stock-level high-frequency trading intensity index from tick-level order data and apply a difference-in-differences design. The regulation significantly improves liquidity by reducing bid-ask spreads and price impact.
A fundus image dataset for intelligent retinopathy of prematurity system - Scientific Data
Abstract Image-based artificial intelligence (AI) systems stand as the major modality for evaluating ophthalmic conditions. However, most of the currently available AI systems are designed for experimental research using single-central datasets. Most of them fell short of application in real-world clinical settings.
Tomography | Free Full-Text | Feasibility of Early Evaluation for the Recurrence of Bladder Cancer after Trans-Urethral Resection: A Comparison between Magnetic Resonance Imaging and Multidetector Computed Tomography
Open AccessArticle by Yiqian Wang 1,2,†, Wei Zhang 1,2,†, Weixiong Xiao 1,2, Shaobin Chen 1,2, Yongbao Wei 1,3 and Min Luo 1,2,* 1 Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350001, China 2 Department of Radiology, Fujian Provincial Hospital, Fuzhou 350001, China 3 Department of Urology, Fujian Provincial Hospital, Fuzhou 350001, China * Author to whom correspondence should be addressed. † These authors contributed equally to this work.
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