INTRODUCTION
The market for medical chatbots and generative artificial intelligence (AI) in healthcare has grown rapidly, driven by substantial economic potential and the capacity of these technologies to reduce healthcare costs [1]. The global generative AI market in healthcare, valued at United States dollar (USD) 1.5 billion in 2023, is projected to reach USD 9.5 billion by 2032, with a compound annual growth rate (CAGR) of 22.5%. Within this field, the healthcare chatbot segment alone is expected to increase from USD 200 million in 2022 to USD 543 million by 2026, at a CAGR of 15.2% [2]. This growth not only reflects industrial and technological advancement but also underscores the strategic importance of AI chatbots as emerging infrastructure for improving healthcare accessibility and clinical efficiency [3].
The evolution of medical chatbots reflects the intersection of technological innovation and clinical need. Table 1 and Fig. 1 summarize this progression. Early conversational programs such as ELIZA and PARRY, developed at the Massachusetts Institute of Technology in the 1960s, simulated psychotherapeutic dialogue and demonstrated the potential of computational interfaces for healthcare communication [4]. In the 1990s, rule-based expert systems emerged, offering basic diagnostic support through symptom input. The 2000s marked a new phase of growth with web- and mobile-based healthcare platforms, including WebMD Symptom Checker, HealthTap, Babylon Health, and Ada Health, which improved access to self-assessment tools and health information for the general public [5]. By emphasizing data structuring and user-interface design, these systems marked a shift from chatbots as simple informationdelivery tools to digital health assistants.
The mid-2010s introduced deep learning and natural-language processing, which transformed chatbots from static question-and-answer systems into interactive medical AI agents capable of contextual understanding and emotional engagement [6]. Systems such as IBM Watson Health and Stanford’s Woebot demonstrated the potential clinical applicability of AI chatbots in decision support and mental health counseling [7]. Since the 2020s, generative AI models, including generative pre-trained transformer (GPT), Med-PaLM, and BioGPT, have achieved increasingly high-quality responses by learning from medical datasets, with growing examples of integration into hospital systems [8]. More recently, the field has shifted toward chatbots capable of recognizing emotions and communicating with greater ethical sensitivity [9]. Together, these developments indicate that medical chatbots have evolved beyond supplementary information tools into increasingly important components of human-AI interaction in healthcare.
In urology, adoption of AI chatbots may help accelerate the transition toward patient-centered care. Urological conditions often involve highly personal and sensitive symptoms, such as urinary incontinence, voiding dysfunction, and sexual health concerns, that may discourage patients from seeking face-toface consultation [10, 11]. In this context, AI chatbots can serve as digital mediators that offer anonymity and psychological safety, enabling patients to share preliminary symptom information more comfortably and recognize when professional medical attention may be needed. In addition, AI chatbots can automate repetitive counseling tasks for clinicians while continuously collecting and analyzing data on symptoms, lifestyle factors, and treatment adherence. They represent 1 component of a rapidly expanding digital health infrastructure, alongside AIdriven imaging analytics, predictive modeling systems, and electronic health record (EHR)-integrated clinical decisionsupport tools already active in urological practice [12]. Their unique capacity for natural-language interaction, however, positions them as particularly accessible and patient-centered interfaces within this ecosystem [13]. Overall, AI chatbots represent a potentially transformative platform for improving clinical efficiency and quality of life among patients receiving urological care.
This review analyzes the current clinical applications and ongoing development of AI chatbot models designed for urology and explores future directions that illustrate how medical chatbots are reshaping the paradigm of patient-centered urological care.
FOR PATIENTS: AI CHATBOTS ACROSS THE UROLOGICAL CARE JOURNEY
Patients’ healthcare experiences follow a continuous trajectory from initial symptom recognition to posttreatment management. Within this continuum, AI chatbots can function as digital interfaces that enhance accessibility, comprehension, and engagement across multiple phases of care. As shown in Fig. 2, this section divides the urological care journey into 5 sequential stages and examines the clinical roles and practical applications of AI chatbots at each stage.
Symptom Checkers
In urology, AI chatbots can serve as screening and early-assessment tools that help patients identify possible conditions and facilitate timely clinical engagement [14]. For example, Kobori et al. [15] developed a chatbot for sexually transmitted infection screening that achieved diagnostic accuracies ranging from 65% to 95%. Notably, 97.7% of users reported an intention to visit a clinic after interacting with the chatbot. This finding suggests that chatbot-based screening may help prompt early medical consultation for sensitive urological conditions in which stigma or embarrassment might otherwise delay care.
Another study involving 300 urological patients demonstrated that AI chatbots can automatically triage mild or non-urgent symptoms and direct patients toward appropriate specialist consultation. Such automated triage may contribute to more efficient allocation of healthcare resources and reduce unnecessary clinical visits [1, 16]. Together, these findings suggest that AI chatbots may have an important role in first-contact digital triage within urological practice.
Patient Education and Counseling
AI chatbots can also facilitate patient education and decisionmaking by providing reliable and comprehensible medical information beyond clinical settings [17]. In prostate cancer education, large language model (LLM)-powered chatbots such as PROSCA and ChatGPT have achieved higher content-quality scores than conventional patient information leaflets [18, 19]. Baumgärtner et al. [20] conducted a randomized controlled trial evaluating a prostate cancer education chatbot and found that patient satisfaction and information retention were significantly higher in the chatbot group; 91% of participants expressed willingness to reuse the tool. In addition, because many educational materials for patients with urological cancer exceed the recommended average readability level for the U.S. population (6th–8th grade), a recent study demonstrated that ChatGPT with specific prompting can help improve accessibility and practical usability [21]. These findings suggest that advanced, domain-specific AI systems can support the generation of personalized and comprehensible patient education resources. They also highlight the potential role of AI chatbots in democratizing health literacy, reducing informational disparities, and empowering patients to participate actively in healthcare decisions.
Lifestyle Change and Conservative Management
For patients with chronic urological conditions, treatment outcomes are strongly influenced by continuity of self-management and adherence to lifestyle modification [22]. AI chatbots can help reinforce these behavioral changes by providing personalized, continuous guidance and feedback. Talyshinskii et al. [1] reported that, among patients with benign prostatic hyperplasia and erectile dysfunction, interaction with an AI chatbot significantly improved self-management scores and decisionmaking efficacy compared with standard care. Similarly, Hose et al. [23] examined a scenario-based interaction between ChatGPT and patients with spinal cord injury and dysfunction for the management of recurrent urinary tract infection symptoms. The chatbot provided reliable, personalized guidance and served as a useful self-management tool, although further personalization and clinical integration were recommended. These studies demonstrate the potential of AI chatbots to promote behavioral change and improve treatment adherence among patients with urological conditions, particularly in long-term disease management.
Clinical Decision Support
AI chatbots have been explored for their ability to analyze patient data and integrate medical records to support evidencebased clinical decision-making. Gabriel et al. linked the European Association of Urology (EAU) Prostate Cancer Guidelines 2023 to ChatGPT-4.0 and, after presenting real clinical scenarios, found that the chatbot proposed management strategies that closely aligned with multidisciplinary team decisions [24]. However, Cocci et al. [25] evaluated 100 urological patient cases by comparing ChatGPT-generated responses with those of expert urologists and found that only 52% of the chatbot’s answers were deemed appropriate. Response quality was particularly low for oncological cases (52.6%) and urological emergencies (11.1%). Similarly, Talyshinskii et al. [26] assessed ChatGPT’s performance using the EAU urolithiasis guidelines and observed that, although it performed satisfactorily for diagnostic queries, its accuracy declined in complex therapeutic decisionmaking tasks. These findings indicate that current AI chatbots are not yet reliable enough to make independent clinical decisions. Nevertheless, under specialist supervision, they may support clinical reasoning and help clinicians remain aligned with urological guidelines.
Posttreatment and Follow-up Care
AI chatbots have demonstrated potential in postoperative monitoring and follow-up care by streamlining clinical workflows and improving the patient experience. In a study evaluating chatbot-generated responses to preoperative and postoperative messages from patients with benign prostatic hyperplasia, the chatbot produced answers that were as accurate as physician responses to common questions regarding preoperative assessment, surgical experience, and postoperative recovery. Notably, subject matter experts rated the chatbot’s messages as more complete and more appropriate in tone, whereas nonmedical volunteers perceived them as more empathic and generally preferable to physicians’ responses [27]. Beyond answering common questions, chatbots can be programmed to conduct post-appointment check-ins, monitor recovery progress, and deliver personalized self-care instructions. By assuming these routines but time-consuming responsibilities, AI chatbots can provide continuous, low-burden patient support while allowing clinicians to focus on more complex aspects of postoperative care.
FOR CLINICIANS: AI CHATBOTS IN UROLOGICAL PRACTICE
Beyond patient engagement, AI chatbots are reshaping clinical work by improving productivity and creating new opportunities in medical education.
Clinical Productivity
AI chatbots have become practical tools for reducing the administrative burden on urologists. In a recent survey of urology healthcare professionals, 83.4% of respondents reported that AI technologies were expected to improve clinical efficiency, with administrative automation ranked as the top benefit [28]. Physicians often devote substantial time to EHR documentation outside direct patient care, and chatbots may help alleviate this burden, allowing clinicians to dedicate more attention to patient interaction. For example, AI chatbots can automatically generate operation notes and discharge summaries based on key clinical data points entered during consultations [29]. In September 2025, Northwestern Medicine Urology introduced an AI-powered scribe system developed with Microsoft and DAX (data analysis expressions). The system captures real-time clinical conversations and automatically drafts structured medical documentation at the point of care. This implementation markedly reduced documentation time and administrative workload for physicians [30].
Similar gains have been observed in other routine tasks. AI chatbots can shorten the time required to review medical records, improve clinic throughput, and streamline repetitive tasks such as appointment scheduling, prescription renewal, and symptom tracking. Across these functions, AI chatbots may meaningfully improve the operation of urological departments.
Medical Education
AI chatbots have also proven valuable in medical education, particularly for supporting urology residents and physicians in activities ranging from examination preparation to educational content generation. When users pose clinical questions, these systems can provide structured explanations and prompt follow-up questions that encourage deeper understanding, features that are particularly suited to self-directed learning [31].
In 2024, GPT-4 and Bing Copilot achieved scores of 77% and 81%, respectively, on the European Board of Urology (EBU) In-Service Assessment, surpassing the passing threshold [32]. Similarly, in a comparative study using 25 andrology clinical cases, ChatGPT-4 outperformed urology residents, with a statistically higher mean score [33]. These findings suggest that LLMs may serve as effective educational adjuncts capable of explaining complex medical concepts clearly. However, discrepancies and factual inaccuracies have been reported even in the most recent models, underscoring the need for continuous refinement and domain-specific fine-tuning [34].
Surgical training is another area in which AI is gaining ground. Trainees can practice in simulated environments without patient risk, thereby improving technical competence and potentially improving clinical outcomes. Within problem-based learning scenarios, chatbots can support learners by providing anatomical context, procedural steps, and clinical decisionmaking guidance during robotic surgery simulation [35].
UROLOGY-SPECIFIC AI CHATBOT MODELS
Europa Uomo × EAU Prostate Cancer Chatbot
As shown in Table 2, the Prostate Cancer Chatbot, jointly developed by Europa Uomo and the EAU, provides a personalized AI counseling service for patients with prostate cancer and their families. It delivers evidence-based information grounded in the latest EAU guidelines and expert knowledge from leading European clinicians. The chatbot responds in real time to questions about prostate cancer diagnosis, treatment options, sideeffect management, and patient support resources.
Available in 95 languages through the Europa Uomo official website (www.europa-uomo.org), the chatbot offers free access through a user-friendly interface and includes emotional-empathy functions designed to reduce anxiety and uncertainty during the treatment process [36]. Following the March 2026 update, the chatbot integrated the latest clinical guidelines and therapeutic data, further establishing itself as a digital healthcare tool for timely patient education and counseling.
UroBot
UroBot, developed in 2024 through a collaboration between the German Cancer Research Center and University Hospital Mannheim, is a specialized urology chatbot that integrates the 2023 EAU Guidelines with retrieval-augmented generation techniques.
To evaluate its performance, researchers compared GPT-3.5, GPT-4, GPT-4o, and UroBot using 200 EBU in-service assessment questions across 10 experimental runs. UroBot achieved the highest mean correct-answer rate (88.4%), outperforming GPT-4o (77.6%). This finding reflects its expert-level consistency on complex clinical queries. The developers emphasized that UroBot is not intended to replace physician judgment; rather, it is designed as a digital copilot that supports clinical decisionmaking and helps maintain guideline consistency in urological practice [32].
UroGPT
UroGPT is an AI-powered chatbot developed by WPE Digital, Inc., a subsidiary of Dornier MedTech in Germany. Designed as a digital healthcare companion for patients with kidney stones, it provides personalized question-and-answer support grounded in verified clinical data from leading U.S. institutions, including Stanford University and University of California, Los Angeles, as well as knowledge aligned with the American Urological Association guidelines. Built on OpenAI’s GPT-4 and customized through Microsoft Azure OpenAI Service, UroGPT is engineered with strict privacy safeguards and full Health Insurance Portability and Accountability Act compliance. The platform delivers end-to-end patient support across the care continuum, including educational resources, lifestyle management guidance, and preoperative checklists.
User evaluations showed that approximately 70%–85% of participants reported easier access to information, improved understanding, and greater usability. The system also achieved a high Net Promoter Score, reflecting strong patient satisfaction and willingness to recommend the tool [37].
Asia-Pacific Region
In the Asia-Pacific region, commercialization and research involving AI chatbots in urology are progressing rapidly [38]. Universities and research institutes in Japan, China, and South Korea are actively developing medical chatbots, diagnostic support systems, and surgical AI assistants, many of which are already being piloted in hospital settings. However, publicly branded or government-endorsed patient chatbots remain relatively limited compared with those in Europe.
In South Korea, examples include hospital-built questionand-answer chatbots, clinic-customized counseling tools, and medical-domain integration of global LLMs such as ChatGPT, Gemini, and Perplexity. These systems are primarily used for responding to patient inquiries, providing lifestyle guidance, and supporting preteleconsultation triage. In China, the release of DeepSeek in 2025 prompted a wave of comparative studies evaluating it against ChatGPT in urological chatbot applications [39, 40]. With expanding governmental support and sustained investment in healthcare AI across the region, Asia is expected to play an increasingly prominent role in the clinical development of urology-focused AI technologies.
BENEFITS AND CHALLENGES
AI chatbots offer tangible benefits across the spectrum of urological care. For patients, they can improve understanding and self-management of urological conditions while providing emotional and informational support, with added benefits of anonymity and accessibility, particularly for sensitive topics such as sexual health. These qualities may encourage earlier clinical visits and help reduce stigma associated with urological conditions. For clinicians, the gains are largely operational. AI chatbots can reduce administrative burden by automating tasks such as patient inquiries, documentation, and triage, thereby allowing clinicians to focus more fully on direct patient care. The 24/7 availability of these systems can also strengthen care continuity in ways that traditional workflows cannot easily replicate. In educational contexts, residents and students may benefit from on-demand explanations and study support tailored to their individual learning needs [14, 22].
However, several critical challenges hinder the widespread adoption of AI chatbots in urology. A key technological concern is hallucination, in which chatbots generate plausible but inaccurate or inappropriate information with undue confidence [41]. Reported accuracy rates for ChatGPT in urology-related queries vary widely, from 41% to 100%, indicating inconsistency across studies. Performance remains inferior to that of human experts, particularly for complex, context-specific clinical decision-making and treatment management [1]. Furthermore, chatbots may reproduce biases embedded in training data, rely on outdated information, or cite irrelevant or non-validated sources [42].
Patient confidentiality and data privacy also pose serious ethical and legal risks, especially when sensitive health data are stored on external cloud servers [43]. Additional barriers include clinicians’ limited training and digital literacy regarding AI tools [44], the high reading ability necessary for chatbotgenerated medical explanations, which often require collegelevel comprehension [45], and patients’ persistent preference for human physicians in emotionally or clinically significant contexts [46]. Finally, the perceived lack of empathy in chatbot interactions continues to challenge patient trust and the integration of these systems into mainstream urological care [27].
CONCLUSIONS
Advances in medical AI are reshaping the paradigm of urological care. As this review has shown, AI chatbots now span much of the patient care continuum, from symptom screening and patient education to postoperative monitoring, while also enhancing clinical productivity and medical education for urologists.
This evolution is far from complete. The fourth generation of medical AI chatbots is expected to move beyond text-based interaction into multimodal intelligent assistants capable of processing diverse clinical inputs, including text, imaging, voice, biosignals, and genomic data [47]. With advances in on-device AI, data processing will increasingly occur within hospital servers or personal devices, addressing longstanding concerns about patient privacy and real-time responsiveness. These developments suggest a transition from informational tools to clinical copilots that connect physicians, nurses, and patients within an integrated care environment.
The vision that emerges is one in which AI chatbots function not as peripheral information providers but as meaningful clinical partners. Realizing this vision, however, requires more than technological advancement. Safe and effective integration will require data standardization, multicenter validation, and clear ethical and legal frameworks [48]. As AI technologies continue to advance, the field of urology must build robust governance structures that ensure responsible, transparent, and patientcentered implementation. At this stage, a cautious, human-supervised approach remains the most prudent path forward as the technology continues to mature.
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