1.7k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Sichuan UniversityCN39 papers
- University of Electronic Science and Technology of ChinaCN10 papers
- West China Medical Center of Sichuan UniversityCN8 papers
- Hong Kong Polytechnic UniversityHK3 papers
- McGill UniversityCA3 papers
- Tongji UniversityCN3 papers
- Chengdu UniversityCN2 papers
- Chinese Academy of Medical Sciences & Peking Union Medical CollegeCN2 papers
- Fudan UniversityCN2 papers
- Group Sense (China)CN2 papers
- Harvard UniversityUS2 papers
- Huazhong University of Science and TechnologyCN2 papers
41 papers
How Do We Research Human-Robot Interaction in the Age of Large Language Models? A Systematic Review
Yufeng Wang, Yuan Xu, Anastasia Nikolova +4
Advances in large language models (LLMs) are profoundly reshaping the field of human-robot interaction (HRI). While prior work has highlighted the technical potential of LLMs, few…
Multi-function Robotized Surgical Dissector for Endoscopic Pulmonary Thromboendarterectomy: Preclinical Study and Evaluation
Runfeng Zhu, Xin Zhong, Qingxiang Zhao +3
Patients suffering chronic severe pulmonary thromboembolism need Pulmonary Thromboendarterectomy (PTE) to remove the thromb and intima located inside pulmonary artery (PA). During…
Self-Paced Learning for Images of Antinuclear Antibodies
Yiyang Jiang, Guangwu Qian, Jiaxin Wu +4
Antinuclear antibody (ANA) testing is a crucial method for diagnosing autoimmune disorders, including lupus, Sjögren's syndrome, and scleroderma. Despite its importance, manual ANA…
GEMeX-RMCoT: An Enhanced Med-VQA Dataset for Region-Aware Multimodal Chain-of-Thought Reasoning
Bo Liu, Xiangyu Zhao, Along He +3
Medical visual question answering aims to support clinical decision-making by enabling models to answer natural language questions based on medical images. While recent advances in…
Selective profiling of non-canonical nucleic acid structures via size-discriminative supramolecular probes
Runyu Shi, Dan Huang, Yanxi Wang +5
Nucleic acids can form diverse non-canonical structures, such as G-quadruplexes (G4s) and i-motifs (iMs), which are critical in biological processes and disease pathways. This stud…
Association in Facial Phenotype, Gene, Disease: A Dataset for Explainable Rare Genetic Diseases Diagnosis
Jie Song, Mengqiao He, Shumin Ren +1
Many rare genetic diseases exhibit recognizable facial phenotypes, which are often used as diagnostic clues. However, current facial phenotype diagnostic models, which are trained…
Real-Time Cell Sorting with Scalable In Situ FPGA-Accelerated Deep Learning
Khayrul Islam, Ryan F. Forelli, Jianzhong Han +6
Precise cell classification is essential in biomedical diagnostics and therapeutic monitoring, particularly for identifying diverse cell types involved in various diseases. Traditi…
Tackling Small Sample Survival Analysis via Transfer Learning: A Study of Colorectal Cancer Prognosis
Yonghao Zhao, Changtao Li, Chi Shu +7
Survival prognosis is crucial for medical informatics. Practitioners often confront small-sized clinical data, especially cancer patient cases, which can be insufficient to induce…
3D Single-shot CEST imaging at 3T Based on True FISP Readout
Yupeng Wu, Qifan Pang, Zhichao Wang +9
To simultaneously fit multiple-pool effects, spectrally selective 3D CEST imaging typically requires single-shot readouts to save time. However, to date, FLASH and EPI have been th…
Beyond the Eye: A Relational Model for Early Dementia Detection Using Retinal OCTA Images
Shouyue Liu, Ziyi Zhang, Yuanyuan Gu +7
Early detection of dementia, such as Alzheimer's disease (AD) or mild cognitive impairment (MCI), is essential to enable timely intervention and potential treatment. Accurate detec…
Advancing Chinese biomedical text mining with community challenges
Hui Zong, Rongrong Wu, Jiaxue Cha +8
Objective: This study aims to review the recent advances in community challenges for biomedical text mining in China. Methods: We collected information of evaluation tasks released…
Advancing bioinformatics with large language models: components, applications and perspectives
Jiajia Liu, Mengyuan Yang, Yankai Yu +4
Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language pro…
Validation of the Practicability of Logical Assessment Formula for Evaluations with Inaccurate Ground-Truth Labels: An Application Study on Tumour Segmentation for Breast Cancer
Yongquan Yang, Hong Bu
The logical assessment formula (LAF) is a new theory proposed for evaluations with inaccurate ground-truth labels (IAGTLs) to assess the predictive models for artificial intelligen…
Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification
Pei Liu, Luping Ji, Xinyu Zhang +1
Given the special situation of modeling gigapixel images, multiple instance learning (MIL) has become one of the most important frameworks for Whole Slide Image (WSI) classificatio…
Experts' cognition-driven safe noisy labels learning for precise segmentation of residual tumor in breast cancer
Yongquan Yang, Jie Chen, Yani Wei +2
Precise segmentation of residual tumor in breast cancer (PSRTBC) after neoadjuvant chemotherapy is a fundamental key technique in the treatment process of breast cancer. However, a…
Towards Real-World Applications of Personalized Anesthesia Using Policy Constraint Q Learning for Propofol Infusion Control
Xiuding Cai, Jiao Chen, Yaoyao Zhu +2
Automated anesthesia promises to enable more precise and personalized anesthetic administration and free anesthesiologists from repetitive tasks, allowing them to focus on the most…
AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images
Pei Liu, Luping Ji, Feng Ye +1
The survival analysis on histological whole-slide images (WSIs) is one of the most important means to estimate patient prognosis. Although many weakly-supervised deep learning mode…
Open Access Dataset for Electromyography based Multi-code Biometric Authentication
Ashirbad Pradhan, Jiayuan He, Ning Jiang
Recently, surface electromyogram (EMG) has been proposed as a novel biometric trait for addressing some key limitations of current biometrics, such as spoofing and liveness. The EM…
Logical Assessment Formula and Its Principles for Evaluations with Inaccurate Ground-Truth Labels
Yongquan Yang
Evaluations with accurate ground-truth labels (AGTLs) have been widely employed to assess predictive models for artificial intelligence applications. However, in some specific fiel…
One-Step Abductive Multi-Target Learning with Diverse Noisy Samples and Its Application to Tumour Segmentation for Breast Cancer
Yongquan Yang, Fengling Li, Yani Wei +4
Recent studies have demonstrated the effectiveness of the combination of machine learning and logical reasoning, including data-driven logical reasoning, knowledge driven machine l…
SSMD: Semi-Supervised Medical Image Detection with Adaptive Consistency and Heterogeneous Perturbation
Hong-Yu Zhou, Chengdi Wang, Haofeng Li +4
Semi-Supervised classification and segmentation methods have been widely investigated in medical image analysis. Both approaches can improve the performance of fully-supervised met…
SCPM-Net: An Anchor-free 3D Lung Nodule Detection Network using Sphere Representation and Center Points Matching
Xiangde Luo, Tao Song, Guotai Wang +5
Lung nodule detection from 3D Computed Tomography scans plays a vital role in efficient lung cancer screening. Despite the SOTA performance obtained by recent anchor-based detector…
SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering
Bo Liu, Li-Ming Zhan, Li Xu +3
Medical visual question answering (Med-VQA) has tremendous potential in healthcare. However, the development of this technology is hindered by the lacking of publicly-available and…
DAN-Net: Dual-Domain Adaptive-Scaling Non-local Network for CT Metal Artifact Reduction
Tao Wang, Wenjun Xia, Yongqiang Huang +5
Metal implants can heavily attenuate X-rays in computed tomography (CT) scans, leading to severe artifacts in reconstructed images, which significantly jeopardize image quality and…