最新刊期
卷 6 ， 期 5 ， 2020
- 摘要：With the increase in the number of the international classification of diseases (ICD) codes,the difficulty and cost of manual coding based on clinical records have greatly increased,and automatic ICD coding technology has attracted widespread attention.A multi-scale residual graph convolution network automatic ICD coding technology was proposed.This technology uses a multi-scale residual network to capture text patterns of different lengths of clinical text and extracts the hierarchical relationship between labels based on the graph convolutional neural network to enhance the ability of automatic coding.The experimental results on the real medical data set MIMIC-III show that the P@k and Micro-F1 of this method are 72.2% and 53.9%,respectively,which significantly improves the prediction performance.关键词：ICD coding;multi-scale;residual network;graph convolutional network735|790|0更新时间：2020-09-15
- 摘要：Sequence alignment and mutation detection are the basic steps of genomic data analysis.They are the premise of subsequent functional analysis,and the most time-consuming steps.In order to effectively deal with the massive genomic big data brought by high-throughput sequencing technology,MPI,OpenMP and other technologies to perform multi-level parallel optimization of sequence alignment algorithm and SNP detection algorithm were used.By testing on different data sets and parallel scales,the core algorithm reached more than 9x speedup,and the parallel efficiency remained above 60% in large-scale test.The improved algorithms obtain good parallel performance and scalability,that effectively improves the ability of genomic big data mutation detection.关键词：sequence alignment;SNP;OpenMP;MPI409|773|0更新时间：2020-09-15
- 摘要：The learning health system (LHS) aims at accelerating the process of knowledge generation,transformation and application in clinical practice.Applying medical big data in LHS to meet the knowledge needs of patients and healthcare decision makers would help to promote the development of precision medicine.Firstly,the current status of medical big data and LHS were reviewed,then the characteristics and challenges of applying medical big data in LHS were analyzed by refering to some typical application cases.Finally,the challenges faced by LHS in China were addressed and the prospect of applying medical big data to LHS in the future was provided.关键词：medical big data;learning health system;medical decision-making1085|1155|0更新时间：2020-09-15
- 摘要：In the study of medical imaging aided diagnosis,researchers often collect a lot of training data coming from different hospitals (named variety fields).But because of the certain field has insufficient training data,the deep learning model would get very poor performance on the test data of this field.To mitigate this problem,a method to study domain adaptation of the difference between male and female brain images based on the generative adversarial network was proposed.The data distribution of different domains was learned and the key features were extracted by using the generative adversarial network,and then the differences between male and female brain images in different domains were studied based on the extracted key features.Experiments show that the method can also achieve more than 80% recognition accuracy in the domain with only a small amount of data involved in training.关键词：deep learning;generative adversarial network;domain adaptation;medical image368|500|0更新时间：2020-09-15
TOPIC：MEDICAL BIG DATA
- 摘要：The effective processing and deep mining analysis of data can provide manufacturers with more effective production scheduling,equipment management and other strategies to affect production yield and efficiency.The processing methods and technologies of multi-source heterogeneous data in the manufacturing process were systematically reviewed.Firstly,the multi-source heterogeneous data content and classification in the manufacturing process was clarified.Secondly,the data processing methods and techniques applied in various stages of data collection,data integration and data analysis in the multi-source heterogeneous data processing were described.And the advantages and disadvantages of various techniques and their applications were analyzed.Finally,the multi-source heterogeneous data processing methods and techniques in the manufacturing process were summarized.And the challenges and development trends were pointed out.关键词：data processing;multi-source heterogeneous data;manufacturing844|1141|0更新时间：2020-09-15
- 摘要：Aspect sentiment analysis based on deep learning is one of the hot spots in natural language processing.Aiming at aspect sentiment,a deep hierarchical attention network model based on aspect sentiment analysis was proposed.The local features of the text and the temporal relationship of different sentences were retained in model through the convolutional neural network,and the emotional features within and between sentences were obtained by using the layered long shortterm memory network (LSTM).Among them,specific aspects of information were added to LSTM and a dynamic control chain was designed to improve the traditional LSTM.A comparative experiment is conducted on the two data sets in SemEval 2014 and the Twitter data set.Compared with the traditional model,the accuracy of sentiment classification of the proposed model increases by about 3%.关键词：deep learning;aspect sentiment;regional convolutional neural network;layered long short-term memory;attention mechanism;dynamic control chain444|830|0更新时间：2020-09-15
- 摘要：In view of the increasing number of people in the digital interaction process of direct or indirect disclosure of privacy issues,the establishment of a set of data security sharing system based on blockchain network,the access control algorithm based on ciphertext-policy attribute-based encryption and the homomorphic encryption algorithm provides reliable chain data sharing were mainly researched.Data sharing on chain architecture for data sharing on the chain was proposed.Finally,simulation experiments were carried out,and the results of experimental data were analyzed.The work effectively solves the problem of malicious parties using the transaction transparency of blockchain for data analysis and ensures the privacy security of user data in the sharing process.关键词：data sharing;blockchain;ciphertext-policy attribute-based encryption;homomorphic encryption;privacy security1567|2039|0更新时间：2020-09-15
STUDY
- 摘要：Blockchain system can build a trusted infrastructure for sharing data between multiple untrusted parties.However,directly uploading original shared data to blockchain is not suitable for large-scale data sharing scenarios.A data sharing architecture where data sharing request and response records are deposited on-chain and original data is transmitted securely off-chain was proposed.The architecture can alleviate the problems of system overload and privacy protection to a certain extent.Finally,with the increase of participating nodes and the data sharing requests and responses to be handled per second,the limitations in distributed storage,consensus protocol,smart contract execution,and query from light clients,directions for further research were proposed,in order to specify the technical bottlenecks that need to be further broken for the existing blockchain system applied to the field of data sharing.关键词：data sharing;data property rights;data tracking;blockchain841|1017|0更新时间：2020-09-15
APPLICATION
- 摘要：Recently,data governance got widespread attention of many industries.Some standards and polices had been published from country and industries,these files defined data governance concept and framework and boost data governance industry development.These files were analysed and some differences between them were identified to help people understand the trends and focus of data governance industry.At same time,some suggestions about how to implement DCMM in the bank industry were provided to help banks to better meet regulatory requirement and improve the maturity level of data management ability.关键词：big data;data quality;data governance;data management capability maturity assessment model;data culture625|978|0更新时间：2020-09-15
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