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...
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| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
20 February 2021
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| In: |
Diagnostics
Year: 2021, Volume: 11, Issue: 2, Pages: 1-20 |
| ISSN: | 2075-4418 |
| DOI: | 10.3390/diagnostics11020354 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.3390/diagnostics11020354 Verlag, lizenzpflichtig, Volltext: https://www.mdpi.com/2075-4418/11/2/354 
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| Author Notes: | Octavian Sabin Tătaru, Mihai Dorin Vartolomei, Jens J. Rassweiler, Oșan Virgil, Giuseppe Lucarelli, Francesco Porpiglia, Daniele Amparore, Matteo Manfredi, Giuseppe Carrieri, Ugo Falagario, Daniela Terracciano, Ottavio de Cobelli, Gian Maria Busetto, Francesco Del Giudice and Matteo Ferro |
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| 520 | |a 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. | ||
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