Artificial Intelligence and Machine Learning in Prostate Cancer Patient Management—Current Trends and Future Perspectives
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,
Matteo Ferro
Affiliations
Octavian Sabin Tătaru
The Institution Organizing University Doctoral Studies (I.O.S.U.D.), George Emil Palade University of Medicine, Pharmacy, Sciences and Technology from Târgu Mureș, 540142 Târgu Mureș, Romania
Mihai Dorin Vartolomei
Department of Cell and Molecular Biology, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology from Târgu Mureș, 540142 Târgu Mureș, Romania
Jens J. Rassweiler
Department of Urology, SLK Kliniken Heilbronn, University of Heidelberg, 74074 Heilbronn, Germany
Oșan Virgil
The Institution Organizing University Doctoral Studies (I.O.S.U.D.), George Emil Palade University of Medicine, Pharmacy, Sciences and Technology from Târgu Mureș, 540142 Târgu Mureș, Romania
Giuseppe Lucarelli
Department of Emergency and Organ Transplantation-Urology, Andrology and Kidney Transplantation Unit, University of Bari, 70124 Bari, Italy
Francesco Porpiglia
Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, 10143 Turin, Italy
Daniele Amparore
Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, 10143 Turin, Italy
Matteo Manfredi
Department of Urology, San Luigi Gonzaga Hospital, University of Turin, Orbassano, 10143 Turin, Italy
Giuseppe Carrieri
Department of Urology and Organ Transplantation, University of Foggia, 71122 Foggia, Italy
Ugo Falagario
Department of Urology and Organ Transplantation, University of Foggia, 71122 Foggia, Italy
Daniela Terracciano
Department of Translational Medical Sciences, University of Naples Federico II, 80131 Naples, Italy
Ottavio de Cobelli
Division of Urology, European Institute of Oncology (IEO)-IRCCS, 20141 Milan, Italy
Gian Maria Busetto
Department of Urology and Renal Transplantation, University of Foggia, Policlinico Riuniti of Foggia, 71122 Foggia, Italy
Francesco Del Giudice
Department of Urology, Policlinico Umberto I, Sapienza University of Rome, 00185 Rome, Italy
Matteo Ferro
Division of Urology, European Institute of Oncology (IEO)-IRCCS, 20141 Milan, Italy
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.
