Matches in SemOpenAlex for { <https://semopenalex.org/work/W2527522263> ?p ?o ?g. }
- W2527522263 endingPage "7083" @default.
- W2527522263 startingPage "7074" @default.
- W2527522263 abstract "Unstructured clinical medical text, as an important part of the electronic health records, is characterized by large quantities and can store substantial disease-related information of patients. Currently, the disease risk assessment model based on the analysis of clinical medical text designs relevant characteristics aiming at certain diseases, and different characteristics are identified from the text using different methods. In this way, changes of disease performance characteristics are difficult to adapt. Furthermore, it is hard to use the risk assessment model in other disease applications. As a result, this paper establishes the universal disease risk assessment model using the data of clinical medical text, conducts the independent study, and extracts disease characteristics from substantial historical data to avoid the limitations designing disease characteristics. First, this paper analyzes the medial clinical text to determine the contents related to the disease characteristics of patients. Second, learn the representation of clinical text with unsupervised learning methods, and study and extract the disease characteristics from the substantial historical data of patients in the convolutional neural network to assess disease risks. Finally, make a contrast experiment of disease risk assessment using the clinical text data of patients with cerebral infarction, patients with pulmonary infection, and patients with coronary atherosclerotic heart disease from the data of a second grade-A hospital in China and related methods. The experiments show that the approach proposed in this paper achieves the disease risk assessment for different diseases with the same structure." @default.
- W2527522263 created "2016-10-07" @default.
- W2527522263 creator A5000432967 @default.
- W2527522263 creator A5004111663 @default.
- W2527522263 creator A5024668079 @default.
- W2527522263 creator A5040645589 @default.
- W2527522263 creator A5040872496 @default.
- W2527522263 creator A5068322072 @default.
- W2527522263 creator A5079127662 @default.
- W2527522263 creator A5080966304 @default.
- W2527522263 date "2016-01-01" @default.
- W2527522263 modified "2023-10-17" @default.
- W2527522263 title "Multiple Disease Risk Assessment With Uniform Model Based on Medical Clinical Notes" @default.
- W2527522263 cites W1148992798 @default.
- W2527522263 cites W1737136247 @default.
- W2527522263 cites W1967738308 @default.
- W2527522263 cites W1979096973 @default.
- W2527522263 cites W1992535127 @default.
- W2527522263 cites W2004910511 @default.
- W2527522263 cites W2015462679 @default.
- W2527522263 cites W2033609349 @default.
- W2527522263 cites W2054106511 @default.
- W2527522263 cites W2054355935 @default.
- W2527522263 cites W2057522896 @default.
- W2527522263 cites W2059145255 @default.
- W2527522263 cites W2060374110 @default.
- W2527522263 cites W2065046698 @default.
- W2527522263 cites W2068503758 @default.
- W2527522263 cites W2100804571 @default.
- W2527522263 cites W2124142667 @default.
- W2527522263 cites W2153966451 @default.
- W2527522263 cites W2158440757 @default.
- W2527522263 cites W2159128662 @default.
- W2527522263 cites W2159756685 @default.
- W2527522263 cites W2172945145 @default.
- W2527522263 cites W2203584209 @default.
- W2527522263 cites W2220600512 @default.
- W2527522263 cites W2227553894 @default.
- W2527522263 cites W2261198379 @default.
- W2527522263 cites W2266199501 @default.
- W2527522263 cites W2277307048 @default.
- W2527522263 cites W2277897549 @default.
- W2527522263 cites W2281611560 @default.
- W2527522263 cites W2296119179 @default.
- W2527522263 cites W2306447822 @default.
- W2527522263 cites W2307646263 @default.
- W2527522263 cites W2313528934 @default.
- W2527522263 cites W2322961426 @default.
- W2527522263 cites W2330246863 @default.
- W2527522263 cites W2334793245 @default.
- W2527522263 cites W2343050074 @default.
- W2527522263 cites W2380127447 @default.
- W2527522263 cites W2413943978 @default.
- W2527522263 cites W2465774274 @default.
- W2527522263 cites W2469579026 @default.
- W2527522263 cites W2498262529 @default.
- W2527522263 cites W2514327853 @default.
- W2527522263 cites W2519923442 @default.
- W2527522263 cites W2524898498 @default.
- W2527522263 cites W3102058818 @default.
- W2527522263 doi "https://doi.org/10.1109/access.2016.2614541" @default.
- W2527522263 hasPublicationYear "2016" @default.
- W2527522263 type Work @default.
- W2527522263 sameAs 2527522263 @default.
- W2527522263 citedByCount "19" @default.
- W2527522263 countsByYear W25275222632017 @default.
- W2527522263 countsByYear W25275222632018 @default.
- W2527522263 countsByYear W25275222632019 @default.
- W2527522263 countsByYear W25275222632020 @default.
- W2527522263 countsByYear W25275222632021 @default.
- W2527522263 countsByYear W25275222632022 @default.
- W2527522263 countsByYear W25275222632023 @default.
- W2527522263 crossrefType "journal-article" @default.
- W2527522263 hasAuthorship W2527522263A5000432967 @default.
- W2527522263 hasAuthorship W2527522263A5004111663 @default.
- W2527522263 hasAuthorship W2527522263A5024668079 @default.
- W2527522263 hasAuthorship W2527522263A5040645589 @default.
- W2527522263 hasAuthorship W2527522263A5040872496 @default.
- W2527522263 hasAuthorship W2527522263A5068322072 @default.
- W2527522263 hasAuthorship W2527522263A5079127662 @default.
- W2527522263 hasAuthorship W2527522263A5080966304 @default.
- W2527522263 hasBestOaLocation W25275222631 @default.
- W2527522263 hasConcept C119857082 @default.
- W2527522263 hasConcept C12174686 @default.
- W2527522263 hasConcept C126322002 @default.
- W2527522263 hasConcept C154945302 @default.
- W2527522263 hasConcept C177713679 @default.
- W2527522263 hasConcept C195910791 @default.
- W2527522263 hasConcept C2779134260 @default.
- W2527522263 hasConcept C38652104 @default.
- W2527522263 hasConcept C41008148 @default.
- W2527522263 hasConcept C71924100 @default.
- W2527522263 hasConceptScore W2527522263C119857082 @default.
- W2527522263 hasConceptScore W2527522263C12174686 @default.
- W2527522263 hasConceptScore W2527522263C126322002 @default.
- W2527522263 hasConceptScore W2527522263C154945302 @default.
- W2527522263 hasConceptScore W2527522263C177713679 @default.
- W2527522263 hasConceptScore W2527522263C195910791 @default.