Urologic Clinics of North America

Endourology 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 of their institutions and prepare themselves to properly critique this new technology...

Bladder 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, treatment planning, quality assessment, and outcome prediction...

The 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 new avenues in RCC research, promising future breakthroughs and innovations that patients and physicians can anticipate...

There 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.

Artificial 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 prostate cancer...

Artificial 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 prognosis of the newly diagnosed patient...

Numerous 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, segmenting, and classifying prostate lesions using open-source databases was performed...

Surgical 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 connection and security, and ethical concerns must be overcome...

Surgical 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 learning algorithms to both evaluate trainee skill and provide real-time and automated feedback, enabling a shortened learning curve for many key procedural skills and ensuring patient safety...

The 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, the authors provide an overview of the recent advances in AI for prostate cancer diagnosis and introduce their next-generation AI model, Green Learning, as a promising solution...

No abstract text is available yet for this article.

No abstract text is available yet for this article.

Transgender and nonbinary (TGNB) patients are a population with unique urologic needs that are often overlooked in urologic training. Most urology residents think that learning to take care of this population is important in their training; however, there is much variation in this educational content within urology residency programs. This review provides information on the current state of teaching regarding the unique needs of caring for TGNB patients as urologists and overviews some basic principles that every urologist should know...

Urologists are experts in the fields of genital and pelvic anatomy, sexual health and reproductive medicine. As such, a working understanding of urologic conditions relevant to transgender and gender diverse patients should be expected within their scope of practice. Herein, we describe an introductory framework for general urologists to grow their knowledge of the appropriate terminology, anatomy, and basic tenets of gender-affirming care to better manage the urologic needs of transgender and gender diverse patients...

Few transgender-specific cancer screening recommendations exist. This review aims to cover current guidelines and practice patterns of cancer screening in transgender patients and, where evidence-based data are lacking, to draw from cisgender screening guidelines to suggest best practices for transgender patients based on anatomic inventory. Sufficient evidence does not exist to determine the long-term effects of gender-affirming hormone therapy on cancer risk. In the future, cancer screening and prevention should be focused on anatomic inventory and high-risk behaviors...

Scales designed for assessing male sexual function may not be suitable for men of all sexual orientations. We reviewed frequently used sexual function scales and examined the item content and documentation of validation. These scales predominantly focus on general sexual function and erection. They lack questions on behaviors relevant to men-who-have-sex-with-men (MSM), such as anal sex, masturbation, or sexual activities outside of committed relationships. Additionally, the validation samples rarely mention inclusion of MSM, revealing a clear gap in the clinical evaluation tools available for MSM, who are experiencing sexual dysfunction from prostate cancer treatment side effects...

This article will review the history of trans and gender diverse individuals in the medical field and suggest relevant content and methods to include in a diversity, equity, and inclusion curriculum. The hope is that the inclusion of these methods will help combat the barriers in place to receiving equitable and fair urologic care.

While diversity and inclusion efforts have increased in urology, comparative analysis of personal statements from 2016-2017 and 2022-2023 residency applications showed few linguistic changes over time by gender or race/ethnicity. These results suggest the need for directed efforts to engage, mentor, and coach females and underrepresented minorities during medical school and the urology application process.

Racism is deeply ingrained in our society with lasting effects within medicine. The COVID-19 pandemic further highlighted racial disparities in the medical field, including in the field of Urology. This has led to investigation regarding the effects of racism on education, patient care, and research within Urology. This article aims to review current literature on the "other pandemic," structural racism, within medicine and specifically urology and provide ways to combat its impact.

The gender gap is an amalgam of gender disparity issues in the workplace ranging from fewer opportunities to network, decreased funding for research, microaggressions, nebulous promotional criteria and difficulty achieving the perception of professionalism because of inherent gender bias. Contributing home factors include more substantial household duties for women typically, spouses who also have a career, and the inherent delay associated with maternity leave for those who choose to have children. This article subdivides gender disparity that impedes promotion into experiences inside and outside the workplace...