The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine
Open accessAbstract
Machine learning (ML), artificial neural networks (ANNs), and deep learning (DL) are all topics that fall under the heading of artificial intelligence (AI) and have gained popularity in recent years. ML involves the application of algorithms to automate decision-making processes using models that have not been manually programmed but have been trained on data. ANNs that are a part of ML aim to simulate the structure and function of the human brain. DL, on the other hand, uses multiple layers of interconnected neurons. This enables the processing and analysis of large and complex databases. In medicine, these techniques are being introduced to improve the speed and efficiency of disease diagnosis and treatment. Each of the AI techniques presented in the paper is supported with an example of a possible medical application. Given the rapid development of technology, the use of AI in medicine shows promising results in the context of patient care. It is particularly important to keep a close eye on this issue and conduct further research in order to fully explore the potential of ML, ANNs, and DL, and bring further applications into clinical use in the future.
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1 retracted
Automatic COVID-19 Lung Infection Segmentation through Modified Unet Model
Shamim, S., Awan, M. J., Zain, A. M., Naseem, U., Mohammed, M. A., & García-Zapirain, B. (2022) · Journal of Healthcare Engineering · doi:10.1155/2022/6566982 · Cited by 39
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Swin-Unet: Unet-like pure transformer for medical image segmentation
Cao, H., Wang, Y., Chen, J., Jiang, D., Zhang, X., Tian, Q., & Wang, M. (2023) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-25066-8_9 · Cited by 5,640
Prototypical Networks for Few-shot Learning
Snell, J., Swersky, K., & Zemel, R. S. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1703.05175 · Cited by 4,755
What is a support vector machine?
Noble, W. S. (2006) · Nature Biotechnology · doi:10.1038/nbt1206-1565 · Cited by 4,301
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Applications of Support Vector Machine (SVM) Learning in Cancer Genomics
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Alzubaidi, L., Bai, J., Al-Sabaawi, A., Santamaría, J., Albahri, A. S., Al-dabbagh, B. S. N., Fadhel, M. A., Manoufali, M., Zhang, J., Al-Timemy, A. H., et al. (2023) · Journal of Big Data · doi:10.1186/s40537-023-00727-2 · Cited by 907
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Cited by
Xu, H., Ma, Y., Zhuang, Y., Zheng, Y., Du, Z., & Zhou, X. (2024) · Scientific Reports · doi:10.1038/s41598-024-71548-3 · Cited by 11
Metadata
- Authors
- Kufel, J., Bargieł-Łączek, K., Kocot, S., Koźlik, M., Bartnikowska, W., Janik, M., Czogalik, Ł., Dudek, P., Magiera, M., Lis, A., Paszkiewicz, I., Nawrat, Z., Cebula, M., & Gruszczyńska, K.
- Venue
- Diagnostics
- Publisher
- MDPI AG
- Published
- 2023-08-03
- Volume
- 13
- Issue
- 15
- Pages
- 2582
- ISSN
- 2075-4418 (ISSN-L)
- OpenAlex
- W4385556979
- Cited by
- 394
- References
- 63
- FWCI
- 13.63
- Type
- journal article
- Language
- en
- Open access
- gold
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- Kufel, J., Bargieł-Łączek, K., Kocot, S., Koźlik, M., Bartnikowska, W., Janik, M., Czogalik, Ł., Dudek, P., Magiera, M., Lis, A., Paszkiewicz, I., Nawrat, Z., Cebula, M., & Gruszczyńska, K. (2023). What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine. Diagnostics. https://doi.org/10.3390/diagnostics13152582
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.