肝脏原发性副神经节瘤1例
Chinese Journal of Diagnostic Pathology(2020)
Abstract
患者自诉于1年前体检发现肝血管瘤,无明显发热,腹痛腹胀,恶心呕吐,心慌胸闷等不适,未予治疗,于2014年3月入院拟手术治疗.既往无特殊病史.CT示肝右后叶圆形低密度强化灶,范围约5.2 cm×4.8 cm,增强早期病灶边缘增强,环绕病灶周围见结节状强化影,延迟扫描强化区逐步向病灶中心移行,肝形态及轮廓正常,胆道未见扩张,脾脏、胰腺及肾上腺未见异常,肝门及腹膜后未见肿大淋巴结(图1).术中探查见腹腔内肝脏颜色质地正常,肿块位于肝脏第8段,大小约6 cm×5 cm,边界清楚,质地软,紧贴下腔静脉,将右半肝完全游离并脱出腹腔,沿肿瘤边缘钝锐结合分离肿瘤,将肿瘤完全切断送病检.
More求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined