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1. chinaXiv:202006.00176 [pdf]

Automated Radiological Impression Generation for Plain Chest X-rays with End to End Deep Learning

Zhang, Shuai; Xin, Xiaoyan; Shen, Jingtao; Guo, Yachong; Wang, Yang; Yang, Xianfeng; Wang, Jun; Zhang, Jian; Zhang, Bing
Subjects: Computer Science >> Other Disciplines of Computer Science

The chest X-Ray (CXR) is the one of the most common clinical exam used to diagnose thoracic diseases and abnormalities. The volume of CXR scans generated daily in hospitals is huge. Therefore, an automated diagnosis system that is able to save the effort of doctors is of great value. At present, the applications of artificial intelligence in CXR diagnosis usually use pattern recognition to classify the scans. However, such methods rely on labeled databases. They are costly and usually have a high error rate. In this work, we built a database containing more than 12,000 CXR scans and radiological reports, and developed a model based on deep convolutional neural network and recurrent network with attention mechanism. The model learns features from the CXR scans and the associated raw radiological reports directly; no additional labeling required. The model provides automated recognition of given scans and generation of impression. The quality of the generated impression was evaluated with both the CIDEr scores and by radiologists as well. The CIDEr scores were found to be around 5.8 on average for the testing dataset. Further blind evaluation suggested a comparable performance against radiologists.

submitted time 2020-06-09 Hits146Downloads77 Comment 0

2. chinaXiv:202004.00026 [pdf]

Learning an Adaptive Model for Extreme Low-light Raw Image Processing

付清旭; 遆晓光; 张雨1
Subjects: Computer Science >> Computer Application Technology

Low-light images suffer from severe noise and low illumination. Current deep learning models that are trained with real-world images have excellent noise reduction, but a ratio parameter must be chosen manually to complete the enhancement pipeline. In this work, we propose an adaptive low-light raw image enhancement network to avoid parameter-handcrafting and to improve image quality. The proposed method can be divided into two sub-models: Brightness Prediction (BP) and Exposure Shifting (ES). The former is designed to control the brightness of the resulting image by estimating a guideline exposure time t 1 . The latter learns to approximate an exposure-shifting operator ES, converting a low-light image with real exposure time t 0 to a noise-free image with guideline exposure time t 1 . Additionally, structural similarity (SSIM) loss and Image Enhancement Vector (IEV) are introduced to promote image quality, and a new Campus Image Dataset (CID) is proposed to overcome the limitations of the existing datasets and to supervise the training of the proposed model. In quantitative tests, it is shown that the proposed method has the lowest Noise Level Estimation (NLE) score compared with BM3D-based low-light algorithms, suggesting a superior denoising performance. Furthermore, those tests illustrate that the proposed method is able to adaptively control the global image brightness according to the content of the image scene. Lastly, the potential application in video processing is briefly discussed.

submitted time 2020-04-14 Hits2720Downloads379 Comment 0

3. chinaXiv:202004.00007 [pdf]

完整的嗅觉神经通路假设及建模

张锦; 田恬恬
Subjects: Computer Science >> Computer Application Technology

嗅觉神经通路研究是嗅觉研究的基础,对脑科学研究同样具有多方面的重要意义。综合已有相关研究成果,探索了完整的嗅觉神经通路假设。该神经通路包括以嗅球层为核心的前端部分、以内嗅皮质为核心的中端部分和以齿状回为核心的后端部分。在此基础上,本文构建了完整的嗅觉神经通路结构模型,并进行了初步分析。

submitted time 2020-04-03 Hits4394Downloads383 Comment 0

4. chinaXiv:202004.00006 [pdf]

一种新的结合仿生学的人工神经网络模型评估研究.pdf

张锦; 舒炫煜; 黄昭彦; 易胜
Subjects: Computer Science >> Other Disciplines of Computer Science

人工神经网络的模型结构与功能分别朝着多样化、智能化趋势发展,但研究者仅从解决问题结果的优劣对模型进行评估是有所欠缺、过于片面的。因此在本文中提出从仿生学的角度构建评估人工神经网络仿生度的指标集,采用定性与定量的方式对模型的仿生度进行整体分析。在定性方面,对模型的神经元方程、网络结构、权重更新原理等方面进行比较分析;在定量方面,基于仿生的角度构建指标集即小世界特性、同步特性及混沌特性,对模型进行分析,分析结果表明,LeNet5模型及BP神经网络具备同步特性,但其与真实生物神经网络仍有一定的距离,而KIII模型在结构上具备一定的小世界特性,其网络内部也表现同步特性及混沌特性,与真实的生物神经网络更为接近。

submitted time 2020-03-29 Hits4323Downloads638 Comment 0

5. chinaXiv:202003.00049 [pdf]

基于自我介绍视频的人格预测技术研究

温业业; 陈德元; 李保滨; 汪晓阳; 刘晓倩; 朱廷劭
Subjects: Psychology >> Applied Psychology

人格影响着个体的工作生活方式,对于个体的心理疏导、职业发展等具有重要指导意义。传统方法通过量表测评人格得分存在个体拒绝回答、盲目作答等问题,近年来随着机器学习的发展为人格识别提供了新的思路。本文使用被试者自我介绍视频和大五人格量表得分,经过关键点提取、特征降维、建模、迭代调参等步骤,针对不同人格维度得到不同的预测模型。测试结果表明,基于自我介绍视频的人格预测模型在各维度都接近或达到中等相关,能够提供无侵扰的人格自动识别,为人格测量提供了新的思路。

submitted time 2020-03-08 Hits12481Downloads847 Comment 0

6. chinaXiv:202003.00048 [pdf]

自监督图像增强网络:仅需低照度图像进行训练

张雨; 遆晓光; 张斌; 王春晖
Subjects: Computer Science >> Other Disciplines of Computer Science

本文提出了一种基于深度学习的自监督低照度图像增强方法。受信息熵理论和Retinex模型的启发,我们提出了一种基于信息熵最大的Retinex模型。利用该模型,一个非常简单的网络可以将照度图和反射图分离开来,且仅用低照度图像就可以进行训练。为了实现自监督学习,我们在模型中引入了一个约束条件:反射图的最大值通道与低照度图像的最大值通道一致,且其熵最大。我们的模型非常简单,不依赖任何精心设计的数据集(即使是一张低照度图像也能完成网络的训练),网络仅需进行分钟级的训练即可实现图像增强。实验证明,该方法在处理速度和效果上均达到了当前最新水平。

submitted time 2020-03-06 Hits10408Downloads536 Comment 0

7. chinaXiv:202002.00063 [pdf]

Perspectives on Active Preventive Measures of Wuhan People against COVID-19 Epidemic at Home: A Comparative Study

zhidong,Xue; Lei,Zhao; Tailang,Yin; Yan,Fu; Zehua,Lyu; yiping,Dang; Yujiang,Zeng; Silou,Huang; Bing,Qu; Hongya,Lyu; Chen,Huang; Zhiyou,Kong; Kepei,Xu; Feipeng,Zhou; Hexun,Dong; He,Hu; Jing,Tang; Senyuan,Xue; Zhixiang,Fang; Jinxiang,Lu
Subjects: Computer Science >> Computer Application Technology

Background:The COVID-19 Epidemic emerged in Wuhan, Hubei province, China. Ever since Wuhan lockdown on January 23rd, mass quarantines were exercised on Wuhan and other epidemic areas of China. We aimed to clarify how ordinary Wuhan people defend against COVID-19 epidemic at home through the Internet survey. Methods:A questionnaire survey, consisting of 30 questions were posted on the Internet. The following aspects were investigated: household preventive measures, self-monitoring of discomfort symptoms, immunity boosting against the epidemic, frequency and reasons of outgoing and mental status of the isolated people. The questionnaire was circulated on Wechat. We marked the areas based on the surveyed network IP addresses and categorized respondents into group A(Wuhan), B(Hubei Province excluding Wuhan ), C, and D based on the epidemic severity of their areas announced by Baidu.com at 17:00 on February 8, 2020. And a comparative study was conducted to illustrate how Wuhan people took the anti-COVID-19 strategies and how efficient these preventive measures were. Findings:In terms of discomfort symptoms, Wuhan, as Group A, had the lowest asymptomatic percentages (70.2%), compared to the average 78.5% (±7%). Considering the three typical symptoms for the COVID-19, i.e., cough, fever and fatigue, Wuhan (9.67%) greatly deviated from the average (7.68%). The fatigue was the most significant factor in the deviation, exceeding the average by 1.35%. In terms of household protection measures, most people or families were able to take effective protection measures with very low frequency of going out, but the percentage of those who took this practice was obviously smaller in Wuhan and Hubei Province. From the aspect of going out, most of the people in Wuhan only went out for shopping and work, with a small number of people for social gathering. In terms of immunity boosting, compared with Group C and D, it was relatively lower in Wuhan. Overall, most people chose to enhance their immunity through regular schedule, exercise, sufficient nutrition. Only 33.44% of people in Group A did not go out, and 59.97% had to go out for living supplies, which was the highest level among the four groups. However, the percentage of people who went out for work and unnecessary activities remains the lowest while 1% of the population went out for public welfare activities, higher than other groups. Worry about the family health topped all the parameters for all the groups. Among them, Wuhan has reached a maximum of 49.61%, higher than the average level of 36.62% (± 10.69%). Mental status except for feeling bored and lonely were the highest in Wuhan. Suggestions:When the epidemic prevention and control is still in a sticky state, and Wuhan started a stricter control measure, the closed management of communities, on Feb 11, 2020, it is expected that our findings can provide some insights into the current household preventive actions and arouse more attentions of the public to some ignored preventive precautions. Unnecessary outgoing should be strictly abandoned. Regular schedule, exercises and nutrition were the top 3 measures participants would choose to enhance their own immunity system. It seems that people in Wuhan would choose nutrition and regular scheduler rather than exercises as the primary immunity-boosting ways. Exercise should be especially advocated as an effective way to enhance the immunity system. In terms of physical condition, people in Wuhan should take more active measures when symptoms occurred. The mentality is also an important aspect requiring intensive attention with the conduct of stricter control management in Wuhan while the rest groups gradually resume to work and ordinary life.

submitted time 2020-02-24 Hits10070Downloads878 Comment 0

8. chinaXiv:202002.00009 [pdf]

一种新型冠状病毒肺炎(COVID-19)药物与天然产物快速发现的计算药理学方法

全源; 梁峰吉; 熊江辉
Subjects: Biology >> Virology

新发传染病爆发流行期间,亟需提出候选药物功效与机制的科学假说。疫苗或新药研发均需要一定时间,因而药物重定位(老药新用)策略有其独特价值。但是新发疾病其病原体、宿主反应的临床数据不充分,制约了候选药物假设的提出。此阶段常根据病人临床特征进行广谱抗病毒药物的尝试。本文借鉴人工智能领域常见的启发式搜索思路,提出一种新方法(aCODE),基于前期有一定疗效提示的广谱抗病毒药,获得其宿主靶蛋白集合,在全基因组尺度上搜索与之相关性最高的基因模块组合,进而对候选化合物(如已批准上市药物、天然产物)进行模式匹配与统计检验排序。本方法可根据临床实践的进展更新输入药物,迭代输出更精准结果,输出的天然产物或中药、药食同源成分结合其它信息后可实施快速测试,形成敏捷研发测试闭环。本方法的第二版更新及其与文献证据的比对分析请参考:http://chinaxiv.org/abs/202002.00024。

submitted time 2020-02-21 Hits17034Downloads1903 Comment 0

9. chinaXiv:202002.00015 [pdf]

人工智能在新型冠状病毒(2019-nCoV)肺炎的应用进展:需求和机遇

王永桂; 李强; 余晴; 杨水化; 徐子怡; 谢天奕; 胡珊
Subjects: Computer Science >> Computer Application Technology

[目的]探究人工智能在新型冠状病毒(2019-nCoV)的诊断、治疗和控制中的应用场景和进展,以利用人工智能为新型冠状病毒肺炎的防控提供助力。 [方法]剖析新型冠状病毒肺炎防控的技术需求,从人工智能基因测序、辅助诊断、远程专家系统、药物筛查与研制等方面,分析当前的应用进展,挖掘应用的机遇。 [结果]中国是新型冠状病毒疫情最严重的国家,存在诸多的技术短板有待科技助力,AI能在疫情防控中发挥出重要的作用,但目前处于初步阶段,缺乏经过验证的落地成果;AI辅助诊断领域重复性研发较多,其他方面研究较少。 [局限]当前应用的数据大部分来自网站报道,如有更多的学术性成果,进展的分析将更全面。 [结论]需要加大投入和调控,在数据、算法和算力共享的基础上,各方面全面展开研发。

submitted time 2020-02-15 Hits17036Downloads1244 Comment 0

10. chinaXiv:202002.00006 [pdf]

运输,病原微生物,文化:2019-nCoV传播的动态图模型

杨晓飞; 徐暾; 贾鹏; 夏涵; 郭立; 叶凯
Subjects: Computer Science >> Computer Application Technology

自从武汉市爆发新型冠状病毒疫情以来,迅速蔓延的事态已经造成300多人死亡,一万多人感染。在中国之外有一百多起病例,影响了全球十几个国家。研究人员已经报道了冠状病毒的全基因组序列,并且正在迅速开发快速诊断试剂盒、有效的治疗方法以及预防性疫苗。最初快速增长的确诊病例触发了武汉及附近城市的封锁。世界各地的科学家尝试建立数学模型来预测未来几天内的感染病例数。但是,交通和文化习俗等主要因素尚未得到足够的权衡。我们的模型并不是为了精确预测感染病例数量,而是旨在模拟公共流行紧急情况下的动态情况以及不同影响因素的贡献。我们希望我们的模型和模拟能够为全球公共卫生机构提供更多的见解和观点信息,以便设计出更好的预防和控制解决方案。

submitted time 2020-02-03 Hits12041Downloads1119 Comment 0

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