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Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives
Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep learning (DL) model is teaching computers to learn by example, something that human beings are doing natu...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924061/ https://www.ncbi.nlm.nih.gov/pubmed/33672608 http://dx.doi.org/10.3390/diagnostics11020354 |
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author | Tătaru, Octavian Sabin Vartolomei, Mihai Dorin Rassweiler, Jens J. Virgil, Oșan Lucarelli, Giuseppe Porpiglia, Francesco Amparore, Daniele Manfredi, Matteo Carrieri, Giuseppe Falagario, Ugo Terracciano, Daniela de Cobelli, Ottavio Busetto, Gian Maria Giudice, Francesco Del Ferro, Matteo |
author_facet | Tătaru, Octavian Sabin Vartolomei, Mihai Dorin Rassweiler, Jens J. Virgil, Oșan Lucarelli, Giuseppe Porpiglia, Francesco Amparore, Daniele Manfredi, Matteo Carrieri, Giuseppe Falagario, Ugo Terracciano, Daniela de Cobelli, Ottavio Busetto, Gian Maria Giudice, Francesco Del Ferro, Matteo |
author_sort | Tătaru, Octavian Sabin |
collection | PubMed |
description | Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep learning (DL) model is teaching computers to learn by example, something that human beings are doing naturally. AI is revolutionizing healthcare. Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. The enormous quantity of data coming from the prostate tumor genome requires fast, reliable and accurate computing power provided by machine learning algorithms. Radiotherapy is an essential part of the treatment of prostate cancer and it is often difficult to predict its toxicity for the patients. Artificial intelligence could have a future potential role in predicting how a patient will react to the therapy side effects. These technologies could provide doctors with better insights on how to plan radiotherapy treatment. The extension of the capabilities of surgical robots for more autonomous tasks will allow them to use information from the surgical field, recognize issues and implement the proper actions without the need for human intervention. |
format | Online Article Text |
id | pubmed-7924061 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79240612021-03-03 Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives Tătaru, Octavian Sabin Vartolomei, Mihai Dorin Rassweiler, Jens J. Virgil, Oșan Lucarelli, Giuseppe Porpiglia, Francesco Amparore, Daniele Manfredi, Matteo Carrieri, Giuseppe Falagario, Ugo Terracciano, Daniela de Cobelli, Ottavio Busetto, Gian Maria Giudice, Francesco Del Ferro, Matteo Diagnostics (Basel) Review Artificial intelligence (AI) is the field of computer science that aims to build smart devices performing tasks that currently require human intelligence. Through machine learning (ML), the deep learning (DL) model is teaching computers to learn by example, something that human beings are doing naturally. AI is revolutionizing healthcare. Digital pathology is becoming highly assisted by AI to help researchers in analyzing larger data sets and providing faster and more accurate diagnoses of prostate cancer lesions. When applied to diagnostic imaging, AI has shown excellent accuracy in the detection of prostate lesions as well as in the prediction of patient outcomes in terms of survival and treatment response. The enormous quantity of data coming from the prostate tumor genome requires fast, reliable and accurate computing power provided by machine learning algorithms. Radiotherapy is an essential part of the treatment of prostate cancer and it is often difficult to predict its toxicity for the patients. Artificial intelligence could have a future potential role in predicting how a patient will react to the therapy side effects. These technologies could provide doctors with better insights on how to plan radiotherapy treatment. The extension of the capabilities of surgical robots for more autonomous tasks will allow them to use information from the surgical field, recognize issues and implement the proper actions without the need for human intervention. MDPI 2021-02-20 /pmc/articles/PMC7924061/ /pubmed/33672608 http://dx.doi.org/10.3390/diagnostics11020354 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Tătaru, Octavian Sabin Vartolomei, Mihai Dorin Rassweiler, Jens J. Virgil, Oșan Lucarelli, Giuseppe Porpiglia, Francesco Amparore, Daniele Manfredi, Matteo Carrieri, Giuseppe Falagario, Ugo Terracciano, Daniela de Cobelli, Ottavio Busetto, Gian Maria Giudice, Francesco Del Ferro, Matteo Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives |
title | Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives |
title_full | Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives |
title_fullStr | Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives |
title_full_unstemmed | Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives |
title_short | Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives |
title_sort | artificial intelligence and machine learning in prostate cancer patient management—current trends and future perspectives |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7924061/ https://www.ncbi.nlm.nih.gov/pubmed/33672608 http://dx.doi.org/10.3390/diagnostics11020354 |
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