Artificial Intelligence and Its Impact on Urological Diseases and Management: A Comprehensive Review of the Literature

Hameed, B. M. Zeeshan; Dhavileswarapu, Aiswarya V. L. S.; Raza, Syed Zahid; Karimi, Hadis; Khanuja, Harneet Singh; Shetty, Dasharathraj K; Ibrahim, Sufyan; Shah, Milap; Naik, Nithesh; Paul, Rahul; Prasad, Bhavan; Somani, Bhaskar K.

doi:10.3390/jcm10091864

Cited by 60 publications

(38 citation statements)

References 81 publications

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“…Artificial intelligence (AI) techniques can be used in that setting [ 23 ]. The applications of AI are vast [ 24 ], and include diagnostic imaging [ 25 ], pathology [ 26 ], segmentation [ 27 ], prognostics [ 28 ], and automatic treatment planning [ 29 , 30 ]. Our model is the first to be trained on a large, prospective, and multicenter cohort of patients.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of an Interpretable Artificial Intelligence Model to Predict 10-Year Prostate Cancer Mortality

Bibault

Hancock

Buyyounouski

et al. 2021

Cancers

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Prostate cancer treatment strategies are guided by risk-stratification. This stratification can be difficult in some patients with known comorbidities. New models are needed to guide strategies and determine which patients are at risk of prostate cancer mortality. This article presents a gradient-boosting model to predict the risk of prostate cancer mortality within 10 years after a cancer diagnosis, and to provide an interpretable prediction. This work uses prospective data from the PLCO Cancer Screening and selected patients who were diagnosed with prostate cancer. During follow-up, 8776 patients were diagnosed with prostate cancer. The dataset was randomly split into a training (n = 7021) and testing (n = 1755) dataset. Accuracy was 0.98 (±0.01), and the area under the receiver operating characteristic was 0.80 (±0.04). This model can be used to support informed decision-making in prostate cancer treatment. AI interpretability provides a novel understanding of the predictions to the users.

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Section: Discussionmentioning

confidence: 99%

Development and Validation of an Interpretable Artificial Intelligence Model to Predict 10-Year Prostate Cancer Mortality

Bibault

Hancock

Buyyounouski

et al. 2021

Cancers

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“…AI in PCa has been applied in different settings such as assessment of benign/malignant lesions, to distinguish significant versus non-significant cancer, defining active surveillance candidates, staging, prediction of response to treatment, and recurrence among others [ 46 , 47 , 48 , 49 , 50 ]. In terms of diagnosis, many studies have reported the advantages of different AI models to provide accurate diagnosis of PCa [ 51 , 52 , 53 , 54 , 55 , 56 ].…”

Section: Mri and Artificial Intelligencementioning

confidence: 99%

MRI and Targeted Biopsy Essential Tools for an Accurate Diagnosis and Treatment Decision Making in Prostate Cancer

et al. 2021

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Prostate cancer (PCa) is one of the most frequent causes of cancer death worldwide. Historically, diagnosis was based on physical examination, transrectal (TRUS) images, and TRUS biopsy resulting in overdiagnosis and overtreatment. Recently magnetic resonance imaging (MRI) has been identified as an evolving tool in terms of diagnosis, staging, treatment decision, and follow-up. In this review we provide the key studies and concepts of MRI as a promising tool in the diagnosis and management of prostate cancer in the general population and in challenging scenarios, such as anteriorly located lesions, enlarged prostates determining extracapsular extension and seminal vesicle invasion, and prior negative biopsy and the future role of MRI in association with artificial intelligence (AI).

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“…The use of AI and ML has been studied in urology within the realm of urologic oncology, but also in other benign subspecialties, including endourology and pediatric urology [ 56 , 59 ]. However, one area that AI/ML may be applicable to all realms of urology is surgical training, particularly in robotic and microsurgical training.…”

Section: Artificial Intelligence Deep Learning and Machine Learningmentioning

confidence: 99%

Technological Advancements in Male Infertility Microsurgery

Punjani

Kang

Lee

et al. 2021

JCM

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There have been significant advancements in male infertility microsurgery over time, and there continues to be significant promise for new and emerging techniques, technologies, and methodologies. In this review, we discuss the history of male infertility and the evolution of microsurgery, the essential role of education and training in male infertility microsurgery, and new technologies in this space. We also review the potentially important role of artificial intelligence (AI) in male infertility and microsurgery.

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Artificial Intelligence and Its Impact on Urological Diseases and Management: A Comprehensive Review of the Literature

Cited by 60 publications

References 81 publications

Development and Validation of an Interpretable Artificial Intelligence Model to Predict 10-Year Prostate Cancer Mortality

Development and Validation of an Interpretable Artificial Intelligence Model to Predict 10-Year Prostate Cancer Mortality

MRI and Targeted Biopsy Essential Tools for an Accurate Diagnosis and Treatment Decision Making in Prostate Cancer

Technological Advancements in Male Infertility Microsurgery

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