Deep Learning for Malaria Diagnosis: Leveraging Convolutional Neural Networks for Accurate Parasite Detection
malaria is one of the most severe diseases worldwide. However, the current diagnostic method that involves examining blood smears under a microscope is unreliable and heavily relies on the examiner's expertise. Recent attempts to use deep-learning algorithms for malaria diagnosis have not prod...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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College of Education for Pure Sciences
2023-09-01
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| Series: | Wasit Journal for Pure Sciences |
| Online Access: | https://wjps.uowasit.edu.iq/index.php/wjps/article/view/205 |
| _version_ | 1827204973092405248 |
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| author | widad kadhim Dr. Mohammed A. Taha Haider D. Abduljabbar |
| author_facet | widad kadhim Dr. Mohammed A. Taha Haider D. Abduljabbar |
| author_sort | widad kadhim |
| collection | DOAJ |
| description |
malaria is one of the most severe diseases worldwide. However, the current diagnostic method that involves examining blood smears under a microscope is unreliable and heavily relies on the examiner's expertise. Recent attempts to use deep-learning algorithms for malaria diagnosis have not produced satisfactory results. But, a new CNN-based machine learning model has been proposed in a research paper that can automatically detect and predict infected cells in thin blood smears with 94.63% accuracy. This model accurately accentuates the region of interest for the stained parasite in the images, which increases its reliability, transparency, and comprehensibility, making it suitable for deployment in healthcare settings.
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| first_indexed | 2024-03-07T18:48:50Z |
| format | Article |
| id | doaj.art-f8ce40729e234f88b44e4ca5fad10b3b |
| institution | Directory Open Access Journal |
| issn | 2790-5233 2790-5241 |
| language | English |
| last_indexed | 2025-03-21T12:00:53Z |
| publishDate | 2023-09-01 |
| publisher | College of Education for Pure Sciences |
| record_format | Article |
| series | Wasit Journal for Pure Sciences |
| spelling | doaj.art-f8ce40729e234f88b44e4ca5fad10b3b2024-06-30T17:32:55ZengCollege of Education for Pure SciencesWasit Journal for Pure Sciences2790-52332790-52412023-09-012310.31185/wjps.205Deep Learning for Malaria Diagnosis: Leveraging Convolutional Neural Networks for Accurate Parasite Detectionwidad kadhim0Dr. Mohammed A. TahaHaider D. Abduljabbarministry of education malaria is one of the most severe diseases worldwide. However, the current diagnostic method that involves examining blood smears under a microscope is unreliable and heavily relies on the examiner's expertise. Recent attempts to use deep-learning algorithms for malaria diagnosis have not produced satisfactory results. But, a new CNN-based machine learning model has been proposed in a research paper that can automatically detect and predict infected cells in thin blood smears with 94.63% accuracy. This model accurately accentuates the region of interest for the stained parasite in the images, which increases its reliability, transparency, and comprehensibility, making it suitable for deployment in healthcare settings. https://wjps.uowasit.edu.iq/index.php/wjps/article/view/205 |
| spellingShingle | widad kadhim Dr. Mohammed A. Taha Haider D. Abduljabbar Deep Learning for Malaria Diagnosis: Leveraging Convolutional Neural Networks for Accurate Parasite Detection Wasit Journal for Pure Sciences |
| title | Deep Learning for Malaria Diagnosis: Leveraging Convolutional Neural Networks for Accurate Parasite Detection |
| title_full | Deep Learning for Malaria Diagnosis: Leveraging Convolutional Neural Networks for Accurate Parasite Detection |
| title_fullStr | Deep Learning for Malaria Diagnosis: Leveraging Convolutional Neural Networks for Accurate Parasite Detection |
| title_full_unstemmed | Deep Learning for Malaria Diagnosis: Leveraging Convolutional Neural Networks for Accurate Parasite Detection |
| title_short | Deep Learning for Malaria Diagnosis: Leveraging Convolutional Neural Networks for Accurate Parasite Detection |
| title_sort | deep learning for malaria diagnosis leveraging convolutional neural networks for accurate parasite detection |
| url | https://wjps.uowasit.edu.iq/index.php/wjps/article/view/205 |
| work_keys_str_mv | AT widadkadhim deeplearningformalariadiagnosisleveragingconvolutionalneuralnetworksforaccurateparasitedetection AT drmohammedataha deeplearningformalariadiagnosisleveragingconvolutionalneuralnetworksforaccurateparasitedetection AT haiderdabduljabbar deeplearningformalariadiagnosisleveragingconvolutionalneuralnetworksforaccurateparasitedetection |