Hepatitis C Virus prediction based on machine learning framework a real-world case study in Egypt
CC BY
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| Định dạng: | Sách |
| Ngôn ngữ: | English |
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Springer
2023
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| Truy cập trực tuyến: | https://link.springer.com/article/10.1007/s10115-023-01851-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8260 |
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oai:localhost:PNK-82602023-04-25T02:14:50Z Hepatitis C Virus prediction based on machine learning framework a real-world case study in Egypt Heba Mamdouh, Farghaly Mahmoud Y., Shams Tarek Abd, El-Hafeez Machine learning SFS CC BY Prediction and classification of diseases are essential in medical science, as it attempts to immune the spread of the disease and discover the infected regions from the early stages. Machine learning (ML) approaches are commonly used for predicting and classifying diseases that are precisely utilized as an efficient tool for doctors and specialists. This paper proposes a prediction framework based on ML approaches to predict Hepatitis C Virus among healthcare workers in Egypt. We utilized real-world data from the National Liver Institute, founded at Menoufiya University (Menoufiya, Egypt). The collected dataset consists of 859 patients with 12 different features. To ensure the robustness and reliability of the proposed framework, we performed two scenarios: the first without feature selection and the second after the features are selected based on sequential forward selection (SFS). 2023-04-25T02:14:50Z 2023-04-25T02:14:50Z 2023 Book https://link.springer.com/article/10.1007/s10115-023-01851-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8260 en application/pdf Springer |
| institution |
Digital Phenikaa |
| collection |
Digital Phenikaa |
| language |
English |
| topic |
Machine learning SFS |
| spellingShingle |
Machine learning SFS Heba Mamdouh, Farghaly Mahmoud Y., Shams Tarek Abd, El-Hafeez Hepatitis C Virus prediction based on machine learning framework a real-world case study in Egypt |
| description |
CC BY |
| format |
Book |
| author |
Heba Mamdouh, Farghaly Mahmoud Y., Shams Tarek Abd, El-Hafeez |
| author_facet |
Heba Mamdouh, Farghaly Mahmoud Y., Shams Tarek Abd, El-Hafeez |
| author_sort |
Heba Mamdouh, Farghaly |
| title |
Hepatitis C Virus prediction based on machine learning framework a real-world case study in Egypt |
| title_short |
Hepatitis C Virus prediction based on machine learning framework a real-world case study in Egypt |
| title_full |
Hepatitis C Virus prediction based on machine learning framework a real-world case study in Egypt |
| title_fullStr |
Hepatitis C Virus prediction based on machine learning framework a real-world case study in Egypt |
| title_full_unstemmed |
Hepatitis C Virus prediction based on machine learning framework a real-world case study in Egypt |
| title_sort |
hepatitis c virus prediction based on machine learning framework a real-world case study in egypt |
| publisher |
Springer |
| publishDate |
2023 |
| url |
https://link.springer.com/article/10.1007/s10115-023-01851-4 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8260 |
| _version_ |
1764177435681619968 |
| score |
8.891787 |