Implementation of intelligent model for pneumonia detection
The advancement of technology in the field of artificial intelligence and neural networks allows us to improve speed and efficiency in the diagnosis of various types of problems. In the last few years, the rise in the field of convolutional neural networks has been particularly noticeable, showing p...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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University North
2019-01-01
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| Series: | Tehnički Glasnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/333675 |
| _version_ | 1797207333534695424 |
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| author | Željko Knok* Klaudio Pap Marko Hrnčić |
| author_facet | Željko Knok* Klaudio Pap Marko Hrnčić |
| author_sort | Željko Knok* |
| collection | DOAJ |
| description | The advancement of technology in the field of artificial intelligence and neural networks allows us to improve speed and efficiency in the diagnosis of various types of problems. In the last few years, the rise in the field of convolutional neural networks has been particularly noticeable, showing promising results in problems related to image processing and computer vision. Given that humans have limited ability to detect patterns in individual images, accurate diagnosis can be a problem for even medical professionals. In order to minimize the number of errors and unintended consequences, computer programs based on neural networks and deep learning principles are increasingly used as assistant tools in medicine. The aim of this study was to develop a model of an intelligent system that receives x-ray image of the lungs as an input parameter and, based on the processed image, returns the possibility of pneumonia as an output. The implementation of this functionality was implemented through transfer learning methodology based on already defined convolution neural network architectures. |
| first_indexed | 2024-04-24T09:21:15Z |
| format | Article |
| id | doaj.art-435f05db2b3e4345bf4fab2cdc054a63 |
| institution | Directory Open Access Journal |
| issn | 1846-6168 1848-5588 |
| language | English |
| last_indexed | 2024-04-24T09:21:15Z |
| publishDate | 2019-01-01 |
| publisher | University North |
| record_format | Article |
| series | Tehnički Glasnik |
| spelling | doaj.art-435f05db2b3e4345bf4fab2cdc054a632024-04-15T15:54:14ZengUniversity NorthTehnički Glasnik1846-61681848-55882019-01-0113431532210.31803/tg-20191023102807Implementation of intelligent model for pneumonia detectionŽeljko Knok*0Klaudio Pap1Marko Hrnčić2Polytechnic of Međimurje in Čakovec, Bana Josipa Jelačica 22a, 40000 Čakovec, CroatiaUniversity of Zagreb, Faculty of Graphic Arts, Getaldićeva 2, 10000 Zagreb, CroatiaZagreb University of Applied Sciences, Mlinarska cesta 38, 10000 Zagreb, CroatiaThe advancement of technology in the field of artificial intelligence and neural networks allows us to improve speed and efficiency in the diagnosis of various types of problems. In the last few years, the rise in the field of convolutional neural networks has been particularly noticeable, showing promising results in problems related to image processing and computer vision. Given that humans have limited ability to detect patterns in individual images, accurate diagnosis can be a problem for even medical professionals. In order to minimize the number of errors and unintended consequences, computer programs based on neural networks and deep learning principles are increasingly used as assistant tools in medicine. The aim of this study was to develop a model of an intelligent system that receives x-ray image of the lungs as an input parameter and, based on the processed image, returns the possibility of pneumonia as an output. The implementation of this functionality was implemented through transfer learning methodology based on already defined convolution neural network architectures.https://hrcak.srce.hr/file/333675computer visionmachine learningneural networkspneumonia |
| spellingShingle | Željko Knok* Klaudio Pap Marko Hrnčić Implementation of intelligent model for pneumonia detection Tehnički Glasnik computer vision machine learning neural networks pneumonia |
| title | Implementation of intelligent model for pneumonia detection |
| title_full | Implementation of intelligent model for pneumonia detection |
| title_fullStr | Implementation of intelligent model for pneumonia detection |
| title_full_unstemmed | Implementation of intelligent model for pneumonia detection |
| title_short | Implementation of intelligent model for pneumonia detection |
| title_sort | implementation of intelligent model for pneumonia detection |
| topic | computer vision machine learning neural networks pneumonia |
| url | https://hrcak.srce.hr/file/333675 |
| work_keys_str_mv | AT zeljkoknok implementationofintelligentmodelforpneumoniadetection AT klaudiopap implementationofintelligentmodelforpneumoniadetection AT markohrncic implementationofintelligentmodelforpneumoniadetection |