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What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine

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 ha...

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Detalles Bibliográficos
Autores principales: Kufel, Jakub, Bargieł-Łączek, Katarzyna, Kocot, Szymon, Koźlik, Maciej, Bartnikowska, Wiktoria, Janik, Michał, Czogalik, Łukasz, Dudek, Piotr, Magiera, Mikołaj, Lis, Anna, Paszkiewicz, Iga, Nawrat, Zbigniew, Cebula, Maciej, Gruszczyńska, Katarzyna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417718/
https://www.ncbi.nlm.nih.gov/pubmed/37568945
http://dx.doi.org/10.3390/diagnostics13152582
Descripción
Sumario: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.