Matches in SemOpenAlex for { <https://semopenalex.org/work/W3212440423> ?p ?o ?g. }
Showing items 1 to 70 of
70
with 100 items per page.
- W3212440423 abstract "Machine Learning is a branch of artificial intelligence widely used in the medical field to analyze high-dimensional medical data and the early detection of certain dangerous diseases. Lung diseases continue to increase the mortality rate in the world. The early and accurate prediction of lung diseases has become a primary necessity to save patient's lives and facilitate doctor's works. This paper focuses on predicting certain chest diseases such as Pneumonia and Asthma using Deep Learning (DL) and Machine Learning (ML) techniques, respectively, the Deep Neural Network (DNN), and the K-nearest Neighbors (KNN) methods. These approaches are evaluated using a private data set from the pulmonary diseases department of Diyarbakir hospital, Turkey. It consists of 212 samples, 38 input characteristics characterize each one. The results obtained showed the effectiveness of these methods to detect pulmonary diseases, particularly the KNN, by giving a detection accuracy of 95% and 94.3% by using the DNN method." @default.
- W3212440423 created "2021-11-22" @default.
- W3212440423 creator A5007340535 @default.
- W3212440423 creator A5022944830 @default.
- W3212440423 date "2021-09-29" @default.
- W3212440423 modified "2023-10-02" @default.
- W3212440423 title "Deep And Machine Learning Towards Pneumonia And Asthma Detection" @default.
- W3212440423 cites W2017034971 @default.
- W3212440423 cites W2470368200 @default.
- W3212440423 cites W2898812155 @default.
- W3212440423 cites W2912392407 @default.
- W3212440423 cites W2947606239 @default.
- W3212440423 cites W3006986403 @default.
- W3212440423 cites W3008699733 @default.
- W3212440423 cites W3090831210 @default.
- W3212440423 cites W3140924497 @default.
- W3212440423 doi "https://doi.org/10.1109/3ict53449.2021.9581963" @default.
- W3212440423 hasPublicationYear "2021" @default.
- W3212440423 type Work @default.
- W3212440423 sameAs 3212440423 @default.
- W3212440423 citedByCount "1" @default.
- W3212440423 countsByYear W32124404232023 @default.
- W3212440423 crossrefType "proceedings-article" @default.
- W3212440423 hasAuthorship W3212440423A5007340535 @default.
- W3212440423 hasAuthorship W3212440423A5022944830 @default.
- W3212440423 hasConcept C108583219 @default.
- W3212440423 hasConcept C119857082 @default.
- W3212440423 hasConcept C126322002 @default.
- W3212440423 hasConcept C154945302 @default.
- W3212440423 hasConcept C202444582 @default.
- W3212440423 hasConcept C2776042228 @default.
- W3212440423 hasConcept C2777914695 @default.
- W3212440423 hasConcept C2984842247 @default.
- W3212440423 hasConcept C33923547 @default.
- W3212440423 hasConcept C41008148 @default.
- W3212440423 hasConcept C50644808 @default.
- W3212440423 hasConcept C58489278 @default.
- W3212440423 hasConcept C71924100 @default.
- W3212440423 hasConcept C9652623 @default.
- W3212440423 hasConceptScore W3212440423C108583219 @default.
- W3212440423 hasConceptScore W3212440423C119857082 @default.
- W3212440423 hasConceptScore W3212440423C126322002 @default.
- W3212440423 hasConceptScore W3212440423C154945302 @default.
- W3212440423 hasConceptScore W3212440423C202444582 @default.
- W3212440423 hasConceptScore W3212440423C2776042228 @default.
- W3212440423 hasConceptScore W3212440423C2777914695 @default.
- W3212440423 hasConceptScore W3212440423C2984842247 @default.
- W3212440423 hasConceptScore W3212440423C33923547 @default.
- W3212440423 hasConceptScore W3212440423C41008148 @default.
- W3212440423 hasConceptScore W3212440423C50644808 @default.
- W3212440423 hasConceptScore W3212440423C58489278 @default.
- W3212440423 hasConceptScore W3212440423C71924100 @default.
- W3212440423 hasConceptScore W3212440423C9652623 @default.
- W3212440423 hasLocation W32124404231 @default.
- W3212440423 hasOpenAccess W3212440423 @default.
- W3212440423 hasPrimaryLocation W32124404231 @default.
- W3212440423 hasRelatedWork W3014300295 @default.
- W3212440423 hasRelatedWork W3164822677 @default.
- W3212440423 hasRelatedWork W4223943233 @default.
- W3212440423 hasRelatedWork W4225161397 @default.
- W3212440423 hasRelatedWork W4312200629 @default.
- W3212440423 hasRelatedWork W4312831135 @default.
- W3212440423 hasRelatedWork W4360585206 @default.
- W3212440423 hasRelatedWork W4364306694 @default.
- W3212440423 hasRelatedWork W4380075502 @default.
- W3212440423 hasRelatedWork W4380086463 @default.
- W3212440423 isParatext "false" @default.
- W3212440423 isRetracted "false" @default.
- W3212440423 magId "3212440423" @default.
- W3212440423 workType "article" @default.