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of 1 736
pro vyhledávání: '"Wang, Ningli"'
Subtle semantic differences in retinal image and text data present great challenges for pre-training visual-language models. Moreover, false negative samples, i.e., image-text pairs having the same semantics but incorrectly regarded as negatives, dis
Externí odkaz:
http://arxiv.org/abs/2408.10894
Autor:
Kang, Mengtian, Hu, Yansong, Gao, Shuo, Liu, Yuanyuan, Meng, Hongbei, Li, Xuemeng, Chen, Xuhang, Zhao, Hubin, Fu, Jing, Hu, Guohua, Wang, Wei, Dai, Yanning, Nathan, Arokia, Smielewski, Peter, Wang, Ningli, Li, Shiming
Childhood myopia constitutes a significant global health concern. It exhibits an escalating prevalence and has the potential to evolve into severe, irreversible conditions that detrimentally impact familial well-being and create substantial economic
Externí odkaz:
http://arxiv.org/abs/2407.21467
The Vision-Language Foundation model is increasingly investigated in the fields of computer vision and natural language processing, yet its exploration in ophthalmology and broader medical applications remains limited. The challenge is the lack of la
Externí odkaz:
http://arxiv.org/abs/2405.14137
Autor:
Wang, Ningling III
Cultured bovine aortic endothelial (BAE) cells were found to synthesize and secrete heparan sulfate proteoglycans (HSPG), which bound basic fibrobalst growth factor (bFGF). bFGF is a known mitogen for vascular smooth muscle cells, and is indicated to
Externí odkaz:
http://hdl.handle.net/10919/36989
http://scholar.lib.vt.edu/theses/available/etd-82197-95920/
http://scholar.lib.vt.edu/theses/available/etd-82197-95920/
Autor:
Liu, Yong, Kang, Mengtian, Gao, Shuo, Zhang, Chi, Liu, Ying, Li, Shiming, Qi, Yue, Nathan, Arokia, Xu, Wenjun, Tang, Chenyu, Occhipinti, Edoardo, Yusufu, Mayinuer, Wang, Ningli, Bai, Weiling, Occhipinti, Luigi
Fundus diseases are major causes of visual impairment and blindness worldwide, especially in underdeveloped regions, where the shortage of ophthalmologists hinders timely diagnosis. AI-assisted fundus image analysis has several advantages, such as hi
Externí odkaz:
http://arxiv.org/abs/2404.13388
Autor:
Wang, Jiaqi, Kang, Mengtian, Liu, Yong, Zhang, Chi, Liu, Ying, Li, Shiming, Qi, Yue, Xu, Wenjun, Tang, Chenyu, Occhipinti, Edoardo, Yusufu, Mayinuer, Wang, Ningli, Bai, Weiling, Gao, Shuo, Occhipinti, Luigi G.
Machine learning-based fundus image diagnosis technologies trigger worldwide interest owing to their benefits such as reducing medical resource power and providing objective evaluation results. However, current methods are commonly based on supervise
Externí odkaz:
http://arxiv.org/abs/2404.13386
Autor:
Qiu, Jianing, Wu, Jian, Wei, Hao, Shi, Peilun, Zhang, Minqing, Sun, Yunyun, Li, Lin, Liu, Hanruo, Liu, Hongyi, Hou, Simeng, Zhao, Yuyang, Shi, Xuehui, Xian, Junfang, Qu, Xiaoxia, Zhu, Sirui, Pan, Lijie, Chen, Xiaoniao, Zhang, Xiaojia, Jiang, Shuai, Wang, Kebing, Yang, Chenlong, Chen, Mingqiang, Fan, Sujie, Hu, Jianhua, Lv, Aiguo, Miao, Hui, Guo, Li, Zhang, Shujun, Pei, Cheng, Fan, Xiaojuan, Lei, Jianqin, Wei, Ting, Duan, Junguo, Liu, Chun, Xia, Xiaobo, Xiong, Siqi, Li, Junhong, Lo, Benny, Tham, Yih Chung, Wong, Tien Yin, Wang, Ningli, Yuan, Wu
We present VisionFM, a foundation model pre-trained with 3.4 million ophthalmic images from 560,457 individuals, covering a broad range of ophthalmic diseases, modalities, imaging devices, and demography. After pre-training, VisionFM provides a found
Externí odkaz:
http://arxiv.org/abs/2310.04992