Rapid bacterial colony classification using deep learning
Bacterial colonies infection is one of the causes of bloodstream disease, and it can be a fatality. Therefore, medical diagnoses require fast identification and classification of organisms. Artificial Intelligence with deep learning (DL) can now be developed as a rapid bacterial classification. The...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Institute of Advanced Engineering and Science
2022
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/37876/ http://umpir.ump.edu.my/id/eprint/37876/1/Rapid%20bacterial%20colony%20classification%20using%20deep%20learning.pdf |
| _version_ | 1848825369124143104 |
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| author | Son Ali, Akbar Kamarul Hawari, Ghazali Habsah, Hasan Zeehaida, Mohamed Wahyu Sapto, Aji Yudhana, Anton |
| author_facet | Son Ali, Akbar Kamarul Hawari, Ghazali Habsah, Hasan Zeehaida, Mohamed Wahyu Sapto, Aji Yudhana, Anton |
| author_sort | Son Ali, Akbar |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Bacterial colonies infection is one of the causes of bloodstream disease, and it can be a fatality. Therefore, medical diagnoses require fast identification and classification of organisms. Artificial Intelligence with deep learning (DL) can now be developed as a rapid bacterial classification. The research aims to combine deep learning and support vector machines (SVM). The ResNet-101 model of the DL algorithm extracted the image’s features using transfer learning then classified by the SVM classifier. According to the experimental results, this model had 99.61% accuracy, 99.58% recall, 99.58% precision, and 99.97% specificity. The technique presented might enhance clinical decision-making. |
| first_indexed | 2025-11-15T03:27:50Z |
| format | Article |
| id | ump-37876 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:27:50Z |
| publishDate | 2022 |
| publisher | Institute of Advanced Engineering and Science |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-378762023-06-27T03:28:30Z http://umpir.ump.edu.my/id/eprint/37876/ Rapid bacterial colony classification using deep learning Son Ali, Akbar Kamarul Hawari, Ghazali Habsah, Hasan Zeehaida, Mohamed Wahyu Sapto, Aji Yudhana, Anton QH Natural history RB Pathology TK Electrical engineering. Electronics Nuclear engineering Bacterial colonies infection is one of the causes of bloodstream disease, and it can be a fatality. Therefore, medical diagnoses require fast identification and classification of organisms. Artificial Intelligence with deep learning (DL) can now be developed as a rapid bacterial classification. The research aims to combine deep learning and support vector machines (SVM). The ResNet-101 model of the DL algorithm extracted the image’s features using transfer learning then classified by the SVM classifier. According to the experimental results, this model had 99.61% accuracy, 99.58% recall, 99.58% precision, and 99.97% specificity. The technique presented might enhance clinical decision-making. Institute of Advanced Engineering and Science 2022-04 Article PeerReviewed pdf en cc_by_sa_4 http://umpir.ump.edu.my/id/eprint/37876/1/Rapid%20bacterial%20colony%20classification%20using%20deep%20learning.pdf Son Ali, Akbar and Kamarul Hawari, Ghazali and Habsah, Hasan and Zeehaida, Mohamed and Wahyu Sapto, Aji and Yudhana, Anton (2022) Rapid bacterial colony classification using deep learning. Indonesian Journal of Electrical Engineering and Computer Science, 26 (1). pp. 352-361. ISSN 2502-4752. (Published) http://doi.org/10.11591/ijeecs.v26.i1.pp352-361 http://doi.org/10.11591/ijeecs.v26.i1.pp352-361 |
| spellingShingle | QH Natural history RB Pathology TK Electrical engineering. Electronics Nuclear engineering Son Ali, Akbar Kamarul Hawari, Ghazali Habsah, Hasan Zeehaida, Mohamed Wahyu Sapto, Aji Yudhana, Anton Rapid bacterial colony classification using deep learning |
| title | Rapid bacterial colony classification using deep learning |
| title_full | Rapid bacterial colony classification using deep learning |
| title_fullStr | Rapid bacterial colony classification using deep learning |
| title_full_unstemmed | Rapid bacterial colony classification using deep learning |
| title_short | Rapid bacterial colony classification using deep learning |
| title_sort | rapid bacterial colony classification using deep learning |
| topic | QH Natural history RB Pathology TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/37876/ http://umpir.ump.edu.my/id/eprint/37876/ http://umpir.ump.edu.my/id/eprint/37876/ http://umpir.ump.edu.my/id/eprint/37876/1/Rapid%20bacterial%20colony%20classification%20using%20deep%20learning.pdf |