Unleashing the power of artificial intelligence for diagnosing and treating infectious diseases: A comprehensive review
Infectious diseases present a global challenge, requiring accurate diagnosis, effective treatments, and preventive measures. Artificial intelligence (AI) has emerged as a promising tool for analysing complex molecular data and improving the diagnosis, treatment, and prevention of infectious diseases...
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| Main Authors: | , , , , , , , , , , , , , , , , , , , |
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| Format: | Book |
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Elsevier,
2023-11-01T00:00:00Z.
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| 100 | 1 | 0 | |a Ali A. Rabaan |e author |
| 700 | 1 | 0 | |a Muhammed A. Bakhrebah |e author |
| 700 | 1 | 0 | |a Jawaher Alotaibi |e author |
| 700 | 1 | 0 | |a Zuhair S. Natto |e author |
| 700 | 1 | 0 | |a Rahaf S. Alkhaibari |e author |
| 700 | 1 | 0 | |a Eman Alawad |e author |
| 700 | 1 | 0 | |a Huda M. Alshammari |e author |
| 700 | 1 | 0 | |a Sara Alwarthan |e author |
| 700 | 1 | 0 | |a Mashael Alhajri |e author |
| 700 | 1 | 0 | |a Mohammed S. Almogbel |e author |
| 700 | 1 | 0 | |a Maha H. Aljohani |e author |
| 700 | 1 | 0 | |a Fadwa S. Alofi |e author |
| 700 | 1 | 0 | |a Nada Alharbi |e author |
| 700 | 1 | 0 | |a Wasl Al-Adsani |e author |
| 700 | 1 | 0 | |a Abdulrahman M. Alsulaiman |e author |
| 700 | 1 | 0 | |a Jehad Aldali |e author |
| 700 | 1 | 0 | |a Fatimah Al Ibrahim |e author |
| 700 | 1 | 0 | |a Reem S. Almaghrabi |e author |
| 700 | 1 | 0 | |a Awad Al-Omari |e author |
| 700 | 1 | 0 | |a Mohammed Garout |e author |
| 245 | 0 | 0 | |a Unleashing the power of artificial intelligence for diagnosing and treating infectious diseases: A comprehensive review |
| 260 | |b Elsevier, |c 2023-11-01T00:00:00Z. | ||
| 500 | |a 1876-0341 | ||
| 500 | |a 10.1016/j.jiph.2023.08.021 | ||
| 520 | |a Infectious diseases present a global challenge, requiring accurate diagnosis, effective treatments, and preventive measures. Artificial intelligence (AI) has emerged as a promising tool for analysing complex molecular data and improving the diagnosis, treatment, and prevention of infectious diseases. Computer-aided detection (CAD) using convolutional neural networks (CNN) has gained prominence for diagnosing tuberculosis (TB) and other infectious diseases such as COVID-19, HIV, and viral pneumonia. The review discusses the challenges and limitations associated with AI in this field and explores various machine-learning models and AI-based approaches. Artificial neural networks (ANN), recurrent neural networks (RNN), support vector machines (SVM), multilayer neural networks (MLNN), CNN, long short-term memory (LSTM), and random forests (RF) are among the models discussed. The review emphasizes the potential of AI to enhance the accuracy and efficiency of diagnosis, treatment, and prevention of infectious diseases, highlighting the need for further research and development in this area. | ||
| 546 | |a EN | ||
| 690 | |a Artificial intelligence | ||
| 690 | |a Machine learning | ||
| 690 | |a Infectious diseases | ||
| 690 | |a Molecular pathology | ||
| 690 | |a Infectious and parasitic diseases | ||
| 690 | |a RC109-216 | ||
| 690 | |a Public aspects of medicine | ||
| 690 | |a RA1-1270 | ||
| 655 | 7 | |a article |2 local | |
| 786 | 0 | |n Journal of Infection and Public Health, Vol 16, Iss 11, Pp 1837-1847 (2023) | |
| 787 | 0 | |n http://www.sciencedirect.com/science/article/pii/S1876034123002897 | |
| 787 | 0 | |n https://doaj.org/toc/1876-0341 | |
| 856 | 4 | 1 | |u https://doaj.org/article/e504ebe636c946d3a7e9c49d223a45b7 |z Connect to this object online. |