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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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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
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author 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
author_facet 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
author_sort Kufel, Jakub
collection PubMed
description 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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spelling pubmed-104177182023-08-12 What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine 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 Diagnostics (Basel) Review 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. MDPI 2023-08-03 /pmc/articles/PMC10417718/ /pubmed/37568945 http://dx.doi.org/10.3390/diagnostics13152582 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
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
What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine
title What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine
title_full What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine
title_fullStr What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine
title_full_unstemmed What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine
title_short What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine
title_sort what is machine learning, artificial neural networks and deep learning?—examples of practical applications in medicine
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10417718/
https://www.ncbi.nlm.nih.gov/pubmed/37568945
http://dx.doi.org/10.3390/diagnostics13152582
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