16 citations · 22 across the 13 of their papers we have counts for
14 papers
Ran Score: a LLM-based Evaluation Score for Radiology Report Generation
Ran Zhang, Yucong Lin, Zhaoli Su +13
Chest X-ray report generation and automated evaluation are limited by poor recognition of low-prevalence abnormalities and inadequate handling of clinically important language, inc…
Scale-Aware Relay and Scale-Adaptive Loss for Tiny Object Detection in Aerial Images
Jinfu Li, Yuqi Huang, Hong Song +5
Recently, despite the remarkable advancements in object detection, modern detectors still struggle to detect tiny objects in aerial images. One key reason is that tiny objects carr…
Sculpting Margin Penalty: Intra-Task Adapter Merging and Classifier Calibration for Few-Shot Class-Incremental Learning
Liang Bai, Hong Song, Jinfu Li +6
Real-world applications often face data privacy constraints and high acquisition costs, making the assumption of sufficient training data in incremental tasks unrealistic and leadi…
MoCTEFuse: Illumination-Gated Mixture of Chiral Transformer Experts for Multi-Level Infrared and Visible Image Fusion
Li Jinfu, Song Hong, Xia Jianghan +5
While illumination changes inevitably affect the quality of infrared and visible image fusion, many outstanding methods still ignore this factor and directly merge the information…
MetaFE-DE: Learning Meta Feature Embedding for Depth Estimation from Monocular Endoscopic Images
Dawei Lu, Deqiang Xiao, Danni Ai +7
Depth estimation from monocular endoscopic images presents significant challenges due to the complexity of endoscopic surgery, such as irregular shapes of human soft tissues, as we…
Efficient Non-Exemplar Class-Incremental Learning with Retrospective Feature Synthesis
Liang Bai, Hong Song, Yucong Lin +5
Despite the outstanding performance in many individual tasks, deep neural networks suffer from catastrophic forgetting when learning from continuous data streams in real-world scen…
Double-Shot 3D Shape Measurement with a Dual-Branch Network for Structured Light Projection Profilometry
Mingyang Lei, Jingfan Fan, Long Shao +6
The structured light (SL)-based three-dimensional (3D) measurement techniques with deep learning have been widely studied to improve measurement efficiency, among which fringe proj…
Hierarchical Pretraining for Biomedical Term Embeddings
Bryan Cai, Sihang Zeng, Yucong Lin +3
Electronic health records (EHR) contain narrative notes that provide extensive details on the medical condition and management of patients. Natural language processing (NLP) of cli…
Harnessing electronic health records for real-world evidence
Jue Hou, Rachel Zhao, Jessica Gronsbell +13
While randomized controlled trials (RCTs) are the gold-standard for establishing the efficacy and safety of a medical treatment, real-world evidence (RWE) generated from real-world…
High-Resolution Boundary Detection for Medical Image Segmentation with Piece-Wise Two-Sample T-Test Augmented Loss
Yucong Lin, Jinhua Su, Yuhang Li +12
Deep learning methods have contributed substantially to the rapid advancement of medical image segmentation, the quality of which relies on the suitable design of loss functions. P…
Knowledge-Enhanced Relation Extraction Dataset
Yucong Lin, Hongming Xiao, Jiani Liu +4
Recently, knowledge-enhanced methods leveraging auxiliary knowledge graphs have emerged in relation extraction, surpassing traditional text-based approaches. However, to our best k…
BIOS: An Algorithmically Generated Biomedical Knowledge Graph
Sheng Yu, Zheng Yuan, Jun Xia +11
Biomedical knowledge graphs (BioMedKGs) are essential infrastructures for biomedical and healthcare big data and artificial intelligence (AI), facilitating natural language process…
Multimodal Learning on Graphs for Disease Relation Extraction
Yucong Lin, Keming Lu, Sheng Yu +2
Objective: Disease knowledge graphs are a way to connect, organize, and access disparate information about diseases with numerous benefits for artificial intelligence (AI). To crea…
High-throughput relation extraction algorithm development associating knowledge articles and electronic health records
Yucong Lin, Keming Lu, Yulin Chen +2
Objective: Medical relations are the core components of medical knowledge graphs that are needed for healthcare artificial intelligence. However, the requirement of expert annotati…