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)
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Abstract
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Bacterial colonies; Deep learning; Transfer Learning; Support Vector Machine |
| Subjects: | Q Science > QH Natural history R Medicine > RB Pathology T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Electrical and Electronic Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 27 Jun 2023 03:28 |
| Last Modified: | 27 Jun 2023 03:28 |
| URI: | http://umpir.ump.edu.my/id/eprint/37876 |
| Download Statistic: | View Download Statistics |
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