Xiyang Liu

发表

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network

Jiewei Jiang, Xiyang Liu, Kai Zhang, 2017, BioMedical Engineering OnLine.

Exploring prognostic indicators in the pathological images of hepatocellular carcinoma based on deep learning

Lei Zhang, Q. Gao, Ya Cao, 2020, Gut.

Prediction of postoperative complications of pediatric cataract patients using data mining

Jiewei Jiang, Xiyang Liu, Kai Zhang, 2019, Journal of Translational Medicine.

Development and validation of deep learning algorithms for scoliosis screening using back images

W. Tan, Xiyang Liu, Kai Zhang, 2019, Communications Biology.

Automatic classification of heterogeneous slit-illumination images using an ensemble of cost-sensitive convolutional neural networks.

Jiewei Jiang, Xiyang Liu, Erping Long, 2020, Annals of translational medicine.

Dense anatomical annotation of slit-lamp images improves the performance of deep learning for the diagnosis of ophthalmic disorders

Chuan Chen, Xiyang Liu, Kai Zhang, 2020, Nature Biomedical Engineering.

Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning

Hongwei Li, Xiyang Liu, Liming Wang, 2021, Nature Communications.

An artificial intelligence platform for the multihospital collaborative management of congenital cataracts

Liming Wang, Xiaoyan Li, Weirong Chen, 2017, Nature Biomedical Engineering.

Artificial intelligence manages congenital cataract with individualized prediction and telehealth computing

Chuan Chen, Xin Liu, Min Li, 2020, npj Digital Medicine.

Localization and diagnosis framework for pediatric cataracts based on slit-lamp images using deep features of a convolutional neural network

Jiangtao Cui, Xiyang Liu, Kai Zhang, 2017, PloS one.

Comparative analysis of image classification methods for automatic diagnosis of ophthalmic images

Jia Zhang, Xiyang Liu, Jing Li, 2017, Scientific Reports.

Artificial intelligence deciphers codes for color and odor perceptions based on large-scale chemoinformatic data

Chuan Chen, Zhiqiang He, Xiyang Liu, 2020, GigaScience.

Dense anatomical annotation of slit-lamp images improves the performance of deep learning for the diagnosis of ophthalmic disorders

Yizhi Liu, Xiyang Liu, Kai Zhang, 2020, Nature Biomedical Engineering.

An Interpretable and Expandable Deep Learning Diagnostic System for Multiple Ocular Diseases: Qualitative Study

Lin Liu, Xiyang Liu, Kai Zhang, 2018, Journal of medical Internet research.

Prediction of postoperative complications of pediatric cataract patients using data mining

Jiewei Jiang, Xiyang Liu, Kai Zhang, 2019, Journal of Translational Medicine.

A human-in-the-loop deep learning paradigm for synergic visual evaluation in children

Chuan Chen, Xiyang Liu, Kai Zhang, 2020, Neural Networks.

Standardization of collection, storage, annotation, and management of data related to medical artificial intelligence

Xiyang Liu, Xiaohang Wu, Haotian Lin, 2021, Intelligent Medicine.

Prediction of Postoperative Complication of Pediatric Cataracts Patients using Data Mining Methods (Preprint)

Xiyang Liu, Kai Zhang, Erping Long, 2018 .

Prototypes-oriented Transductive Few-shot Learning with Conditional Transport

Xiyang Liu, Liming Wang, Long Tian, 2023, ArXiv.

Predicting the progression of ophthalmic disease based on slit-lamp images using a deep temporal sequence network

Jiangtao Cui, Shuai Wang, Lin Liu, 2018, PloS one.

Automatic classification of heterogeneous slit-illumination 1 images using an ensemble of cost-sensitive convolutional 2 neural networks

Jiewei Jiang, Xiyang Liu, Erping Long, 2020 .

Artificial intelligence deciphers codes for color and odor perceptions based on large-scale chemoinformatic data

Xiyang Liu, Kai Zhang, Erping Long, 2020, GigaScience.