The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging: A Balanced Alternative to Deep Learning and Radiomics
Urol Clin North Am. 2024 Feb;51(1):1-13. doi: 10.1016/j.ucl.2023.08.001. Epub 2023 Aug 30.ABSTRACTThe application of artificial intelligence (AI) on prostate magnetic resonance imaging (MRI) has shown promising results. Several AI systems have been developed to automatically analyze prostate MRI for segmentation, cancer detection, and region of interest characterization, thereby assisting clinicians in their decision-making process. Deep learning, the current trend in imaging AI, has limitations including the lack of transparency "black box", large data processing, and excessive energy consumption. In this narrative review...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Masatomo Kaneko Vasileios Magoulianitis Lorenzo Storino Ramacciotti Alex Raman Divyangi Paralkar Andrew Chen Timothy N Chu Yijing Yang Jintang Xue Jiaxin Yang Jinyuan Liu Donya S Jadvar Karanvir Gill Giovanni E Cacciamani Chrysostomos L Nikias Vinay Dudda Source Type: research

Surgical Artificial Intelligence in Urology: Educational Applications
Urol Clin North Am. 2024 Feb;51(1):105-115. doi: 10.1016/j.ucl.2023.06.003. Epub 2023 Jul 27.ABSTRACTSurgical education has seen immense change recently. Increased demand for iterative evaluation of trainees from medical school to independent practice has led to the generation of an overwhelming amount of data related to an individual's competency. Artificial intelligence has been proposed as a solution to automate and standardize the ability of stakeholders to assess the technical and nontechnical abilities of a surgical trainee. In both the simulation and clinical environments, evidence supports the use of machine learni...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Mitchell G Goldenberg Source Type: research

Artificial Intelligence in Urology: Current Status and Future Perspectives
Urol Clin North Am. 2024 Feb;51(1):117-130. doi: 10.1016/j.ucl.2023.06.005. Epub 2023 Jul 30.ABSTRACTSurgical fields, especially urology, have shifted increasingly toward the use of artificial intelligence (AI). Advancements in AI have created massive improvements in diagnostics, outcome predictions, and robotic surgery. For robotic surgery to progress from assisting surgeons to eventually reaching autonomous procedures, there must be advancements in machine learning, natural language processing, and computer vision. Moreover, barriers such as data availability, interpretability of autonomous decision-making, Internet conn...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Rayyan Abid Ahmed A Hussein Khurshid A Guru Source Type: research

Comprehensive Assessment of MRI-based Artificial Intelligence Frameworks Performance in the Detection, Segmentation, and Classification of Prostate Lesions Using Open-Source Databases
Urol Clin North Am. 2024 Feb;51(1):131-161. doi: 10.1016/j.ucl.2023.08.003. Epub 2023 Sep 11.ABSTRACTNumerous MRI-based artificial intelligence (AI) frameworks have been designed for prostate cancer lesion detection, segmentation, and classification via MRI as a result of intrareader and interreader variability that is inherent to traditional interpretation. Open-source data sets have been released with the intention of providing freely available MRIs for the testing of diverse AI frameworks in automated or semiautomated tasks. Here, an in-depth assessment of the performance of MRI-based AI frameworks for detecting, segmen...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Lorenzo Storino Ramacciotti Jacob S Hershenhouse Daniel Mokhtar Divyangi Paralkar Masatomo Kaneko Michael Eppler Karanvir Gill Vasileios Mogoulianitis Vinay Duddalwar Andre L Abreu Inderbir Gill Giovanni E Cacciamani Source Type: research

Artificial Intelligence and Pathomics: Prostate Cancer
Urol Clin North Am. 2024 Feb;51(1):15-26. doi: 10.1016/j.ucl.2023.06.001. Epub 2023 Jul 25.ABSTRACTArtificial intelligence (AI) has the potential to transform pathologic diagnosis and cancer patient management as a predictive and prognostic biomarker. AI-based systems can be used to examine digitally scanned histopathology slides and differentiate benign from malignant cells and low from high grade. Deep learning models can analyze patient data from individual or multimodal combinations and identify patterns to be used to predict the response to different therapeutic options, the risk of recurrence or progression, and the ...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Puria Azadi Moghadam Ali Bashashati S Larry Goldenberg Source Type: research

Genomics and Artificial Intelligence: Prostate Cancer
Urol Clin North Am. 2024 Feb;51(1):27-33. doi: 10.1016/j.ucl.2023.06.006. Epub 2023 Jul 31.ABSTRACTArtificial intelligence (AI) is revolutionizing prostate cancer genomics research. By leveraging machine learning and deep learning algorithms, researchers can rapidly analyze vast genomic datasets to identify patterns and correlations that may be missed by traditional methods. These AI-driven insights can lead to the discovery of novel biomarkers, enhance the accuracy of diagnosis, and predict disease progression and treatment response. As such, AI is becoming an indispensable tool in the pursuit of personalized medicine for...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Elyssa Y Wong Timothy N Chu Seyedeh-Sanam Ladi-Seyedian Source Type: research

Radiomics and Artificial Intelligence: Renal Cell Carcinoma
Urol Clin North Am. 2024 Feb;51(1):35-45. doi: 10.1016/j.ucl.2023.06.007. Epub 2023 Jul 28.ABSTRACTThere is a clinical need for accurate diagnosis and prognostication of kidney cancer using imaging. Radiomics and deep learning methods applied to imaging have shown promise in tasks such as tumor segmentation, classification, staging, and grading, as well as assessment of preoperative scores and correlation with tumor biomarkers. Artificial intelligence is also expected to play a significant role in advancing personalized medicine for the treatment of renal cell carcinoma.PMID:37945101 | DOI:10.1016/j.ucl.2023.06.007 (Source...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Alex G Raman David Fisher Felix Yap Assad Oberai Vinay A Duddalwar Source Type: research

Artificial Intelligence in Pathomics and Genomics of Renal Cell Carcinoma
Urol Clin North Am. 2024 Feb;51(1):47-62. doi: 10.1016/j.ucl.2023.06.002. Epub 2023 Jul 21.ABSTRACTThe integration of artificial intelligence (AI) with histopathology images and gene expression patterns has led to the emergence of the dynamic fields of pathomics and genomics. These fields have revolutionized renal cell carcinoma (RCC) diagnosis and subtyping and improved survival prediction models. Machine learning has identified unique gene patterns across RCC subtypes and grades, providing insights into RCC origins and potential treatments, as targeted therapies. The combination of pathomics and genomics using AI opens n...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: J Everett Knudsen Joseph M Rich Runzhuo Ma Source Type: research

Bladder Cancer and Artificial Intelligence: Emerging Applications
Urol Clin North Am. 2024 Feb;51(1):63-75. doi: 10.1016/j.ucl.2023.07.002. Epub 2023 Aug 25.ABSTRACTBladder cancer is a common and heterogeneous disease that poses a significant burden to the patient and health care system. Major unmet needs include effective early detection strategy, imprecision of risk stratification, and treatment-associated morbidities. The existing clinical paradigm is imprecise, which results in missed tumors, suboptimal therapy, and disease progression. Artificial intelligence holds immense potential to address many unmet needs in bladder cancer, including early detection, risk stratification, treatm...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Mark A Laurie Steve R Zhou Md Tauhidul Islam Eugene Shkolyar Lei Xing Joseph C Liao Source Type: research

Surgical Artificial Intelligence: Endourology
Urol Clin North Am. 2024 Feb;51(1):77-89. doi: 10.1016/j.ucl.2023.06.004. Epub 2023 Jul 31.ABSTRACTEndourology is ripe with information that includes patient factors, laboratory tests, outcomes, and visual data, which is becoming increasingly complex to assess. Artificial intelligence (AI) has the potential to explore and define these relationships; however, humans might not be involved in the input, analysis, or even determining the methods of analysis. Herein, the authors present the current state of AI in endourology and highlight the need for urologists to share their proposed AI solutions for reproducibility outside o...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Zachary E Tano Andrei D Cumpanas Antonio R H Gorgen Allen Rojhani Jaime Altamirano-Villarroel Jaime Landman Source Type: research

Artificial Intelligence in Pediatric Urology
Urol Clin North Am. 2024 Feb;51(1):91-103. doi: 10.1016/j.ucl.2023.08.002. Epub 2023 Sep 15.ABSTRACTApplication of artificial intelligence (AI) is one of the hottest topics in medicine. Unlike traditional methods that rely heavily on statistical assumptions, machine learning algorithms can identify highly complex patterns from data, allowing robust predictions. There is an abundance of evidence of exponentially increasing pediatric urologic publications using AI methodology in recent years. While these studies show great promise for better understanding of disease and patient care, we should be realistic about the challeng...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Hsin-Hsiao Scott Wang Ranveer Vasdev Caleb P Nelson Source Type: research

Artificial Intelligence in Urology: The Final Frontier?
Urol Clin North Am. 2024 Feb;51(1):xi-xii. doi: 10.1016/j.ucl.2023.08.004. Epub 2023 Sep 1.NO ABSTRACTPMID:37945106 | DOI:10.1016/j.ucl.2023.08.004 (Source: The Urologic Clinics of North America)
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Kevin R Loughlin Source Type: research

A Glance at the Present and Future of Artificial Intelligence in Urology
Urol Clin North Am. 2024 Feb;51(1):xiii. doi: 10.1016/j.ucl.2023.06.017. Epub 2023 Jul 19.NO ABSTRACTPMID:37945107 | DOI:10.1016/j.ucl.2023.06.017 (Source: The Urologic Clinics of North America)
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Andrew J Hung Source Type: research

The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging: A Balanced Alternative to Deep Learning and Radiomics
Urol Clin North Am. 2024 Feb;51(1):1-13. doi: 10.1016/j.ucl.2023.08.001. Epub 2023 Aug 30.ABSTRACTThe application of artificial intelligence (AI) on prostate magnetic resonance imaging (MRI) has shown promising results. Several AI systems have been developed to automatically analyze prostate MRI for segmentation, cancer detection, and region of interest characterization, thereby assisting clinicians in their decision-making process. Deep learning, the current trend in imaging AI, has limitations including the lack of transparency "black box", large data processing, and excessive energy consumption. In this narrative review...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Masatomo Kaneko Vasileios Magoulianitis Lorenzo Storino Ramacciotti Alex Raman Divyangi Paralkar Andrew Chen Timothy N Chu Yijing Yang Jintang Xue Jiaxin Yang Jinyuan Liu Donya S Jadvar Karanvir Gill Giovanni E Cacciamani Chrysostomos L Nikias Vinay Dudda Source Type: research

Surgical Artificial Intelligence in Urology: Educational Applications
Urol Clin North Am. 2024 Feb;51(1):105-115. doi: 10.1016/j.ucl.2023.06.003. Epub 2023 Jul 27.ABSTRACTSurgical education has seen immense change recently. Increased demand for iterative evaluation of trainees from medical school to independent practice has led to the generation of an overwhelming amount of data related to an individual's competency. Artificial intelligence has been proposed as a solution to automate and standardize the ability of stakeholders to assess the technical and nontechnical abilities of a surgical trainee. In both the simulation and clinical environments, evidence supports the use of machine learni...
Source: The Urologic Clinics of North America - November 9, 2023 Category: Urology & Nephrology Authors: Mitchell G Goldenberg Source Type: research