机器人

Artificial intelligence (AI) and machine learning (ML) technologies are rapidly transforming telesurgery by enhancing robotic-assisted surgical systems, remote surgical communication, image-guided interventions, and intelligent decision-making. The integration of AI-driven algorithms with telesurgical platforms has accelerated research activity across medicine, robotics, engineering, and computer science. However, the global research landscape, collaborative structure, and emerging thematic trends of AI- and ML-enabled telesurgery remain insufficiently explored. Therefore, the present study aimed to perform a comprehensive bibliometric and knowledge mapping analysis of global research on AI and ML applications in robotic, teleoperated, and remote surgery published between 2015 and 2025. A bibliometric analysis was conducted using the Scopus database on 28 May 2026. Articles published between 2015 and 2025 related to AI, machine learning, robotic surgery, teleoperation, and telesurgery were retrieved using predefined search terms. Only English-language research articles were included. Bibliometric indicators including annual publication trends, citation analysis, leading journals, productive authors, institutions, funding agencies, country collaborations, co-citation analysis, and keyword co-occurrence analysis were evaluated. Visualization and network mapping were performed using VOSviewer software (version 1.6.20). A total of 2,201 publications were identified from 112 countries. Scientific output demonstrated substantial exponential growth, increasing from 85 publications in 2015 to 1,167 publications in 2025. Medicine (29%), computer science (24%), and engineering (20%) represented the dominant research areas. Journal of Robotic Surgery emerged as the leading publication source, while China and the United States were identified as the most influential contributing countries. Keyword co-occurrence analysis highlighted major research themes including robotic surgery, deep learning, machine learning, intelligent robotics, teleoperation, and minimally invasive surgery. Overlay visualization demonstrated a recent shift toward AI-driven autonomous systems, computer vision, surgical workflow analysis, and intelligent robotic platforms. Co-citation analysis further revealed strong interdisciplinary foundations involving surgical sciences, robotics, computer vision, and advanced deep learning methodologies. Research on AI and ML applications in robotic, teleoperated, and remote surgery has grown rapidly over the last decade and is increasingly characterized by strong interdisciplinary collaboration and technological innovation. Emerging trends suggest a transition from conventional robotic-assisted surgery toward intelligent, data-driven, and semi-autonomous telesurgical systems. The findings of this bibliometric study provide valuable insights into the evolving scientific landscape of intelligent telesurgery and may support future research, clinical translation, technological development, and policy planning in robotic-assisted remote surgical care.

Learning curves for robotic total knee arthroplasty (TKA) have been widely described during the initial adoption of robotic technology. However, it remains unclear whether robotic surgical proficiency is platform-specific or transferable between systems based on different modelling paradigms. The purpose of this study was to evaluate whether an experienced robotic surgeon demonstrates a measurable learning curve when transitioning from imageless to CT-based robotic TKA. A senior surgeon with experience exceeding 1000 robotic knee arthroplasties performed using imagel-ess platforms transitioned to a CT-based robotic TKA system. The first 25 consecutive CT-based robotic TKAs were prospectively analysed. Operative time and postoperative radiographic alignment (HKA, LDFA, MPTA, tibial slope) were assessed. Learning curve dynamics were evaluated using cumulative sum (CUSUM) and segmented regression analyses. Radiographic outliers were defined as deviations greater than 2&#xb0; from the planned target. Operative time decreased from 65&#xa0;min in the first case to a steady-state mean of 55&#x2009;&#xb1;&#x2009;3&#xa0;min (95% CI 53.8-56.2) by case 3, corresponding to a 15.4% reduction. Continuous CUSUM demonstrated an inflection point at case 2, confirmed by segmented regression (p&#x2009;<&#x2009;0.05). Mean postoperative alignment was 0.7&#xb0; &#xb1; 1.2&#xb0; for HKA, 88.5&#xb0; &#xb1; 1.1&#xb0; for LDFA, 87.8&#xb0; &#xb1; 1.2&#xb0; for MPTA, and 4.8&#xb0; &#xb1; 0.7&#xb0; for tibial slope. No radiographic outliers (>&#x2009;2&#xb0;) were observed after case 2. In an experienced robotic surgeon, transition from imageless to CT-based robotic TKA was not associated with a clinically relevant learning curve. Operative efficiency stabilised rapidly and radiographic alignment accuracy was maintained from the earliest procedures. These findings suggest that robotic TKA proficiency may be transferable across platforms, although confirmation through multicentre comparative studies remains necessary. Level IV.

The integration of robots into clinical practice requires careful consideration of their alignment with nursing workflows, patient needs, and clinical contexts. This scoping review aimed to support effective technology adoption by systematically identifying and classifying how robots are used in hospital-based nursing practice using standardized nursing terminology. A scoping review following Arksey and O'Malley's five-stage framework. A structured search was conducted in five peer-reviewed databases (PubMed, Web of Science, Cochrane Library, CINAHL, and EMBASE) for studies published between January 2019 and July 24, 2025. The data were analyzed to classify the types of nursing tasks supported by the robots. Robotic functions were classified into direct care, indirect care, and associated work using standardized nursing terminology, Hurst's framework, and the Clinical Care Classification system to provide a codified and structured analysis of nursing tasks. A total of 40 studies were included in the final review. Thirty-three focused on direct care with robots, primarily supporting psychological, physiological, and functional care. The key interventions included coping support, emotional support, infection control, and vital sign monitoring. Only one study involved indirect care, and nine focused on associated work, such as errands and cleaning. Robots are primarily used for direct care, such as emotional support and monitoring, while their role in indirect care-requiring professional judgment including documentation-remains limited. This suggests that future development should prioritize user-centered designs and ethical guidelines aligned with actual clinical needs. Properly implemented robotic technology will serve as a strategic tool to enhance nursing efficiency and improve practice environments amidst chronic workforce shortages. By categorizing robotic functions using standardized nursing terminology, this review offers a structured understanding of how robots can support nursing. These insights help identify tasks that can be delegated to robots during crises, such as pandemics or staffing shortages, allowing nurses to focus on essential patient care.

Robotic-assisted arthroplasty has been introduced to improve the precision and reproducibility of implant positioning in joint replacement surgery. While clinical and economic evaluations continue to expand, little is known about patient perceptions of this technology, and no Irish data currently exist. This study evaluates patient awareness, attitudes, and expectations regarding robotic-assisted joint replacement in an Irish tertiary orthopaedic center. A cross-sectional paper-based survey was administered to adult patients attending elective orthopaedic outpatient clinics between August and November 2025. The questionnaire assessed awareness, perceived risks and benefits, willingness to undergo robotic-assisted surgery, and views on surgeon vs robot control using yes/no questions and 0-10 Likert scales. Descriptive and comparative analyses were performed. A total of 117 patients participated. Awareness of robotic-assisted arthroplasty was modest, with 38.5% reporting prior knowledge of the technology. Most patients (87.2%) wished to be informed if a robot were involved in their operation, yet only 11.1% would change surgeons to access robotic-assisted surgery. Awareness significantly influenced expectations: those who had heard of robotics anticipated better outcomes (6.5 &#xb1; 1.8 vs 5.0 &#xb1; 2.1, P < .001), less postoperative pain (4.8 &#xb1; 1.5 vs 5.7 &#xb1; 1.8, P = .006), and lower risk (4.7 &#xb1; 2.1 vs 5.8 &#xb1; 2.3, P = .019) than those unaware. Perceptions of invasiveness, operative time, cost, recovery, and robot independence did not significantly differ. Age did not influence awareness or perception across any domain. This first Irish study demonstrates low awareness and mixed optimism toward robotic arthroplasty. Prior awareness is associated with more favorable expectations, while trust in the surgeon remains central.

To summarize and evaluate the core components, functional modules, and developmental challenges of intelligent oral examination robots, and to clarify their potential clinical relevance as well as the mechanisms by which robotics and artificial intelligence can enhance diagnostic efficiency and standardization in dentistry. This study employed a systematic literature review methodology, retrieving relevant publications from the PubMed and ScienceDirect databases up to September 2025. The search strategy utilized Boolean operators to combine keywords such as 'robot,' 'AI,' 'oral diagnosis,' and 'intraoral scanner,' aiming to comprehensively cover the fields of robotic technology, oral diagnostics, artificial intelligence, and related sensing technologies. The initial search yielded approximately 1,027 articles, of which 134 were ultimately included after screening. Inclusion criteria comprised studies related to oral robotic technologies, applications of artificial intelligence in diagnosis, and robotic navigation, while exclusion criteria included non-peer-reviewed publications and studies with insufficient methodological descriptions. A combined approach of narrative review and critical analysis was adopted, with a focus on key technical domains, including hardware architecture, software integration, multimodal perception systems, and force feedback mechanisms. The analysis identified several key technological components of intelligent oral examination robots, including high-resolution intraoral imaging systems, multimodal data fusion frameworks, force-sensing and adaptive control technologies, automated navigation systems, and AI-driven data-processing algorithms. These systems contribute to improved image acquisition accuracy, standardized diagnostic procedures, enhanced data management, and optimized clinical workflow. However, challenges remain in system integration, safety assurance, real-time responsiveness, and clinical validation. Current technological advances suggest that intelligent oral examination robots have significant potential to reduce clinician workload, improve diagnostic accuracy, and enhance consistency in oral examinations. Continued refinement in hardware-software integration, safety mechanisms, and clinical adaptability will be essential for broader implementation. Intelligent oral examination robots may significantly improve diagnostic quality through automation, standardized data acquisition, and enhanced imaging capabilities. Their application could facilitate early disease detection, improve patient management, and streamline clinical workflows in modern dental practice.

The introduction of robotic-assisted abdominal surgery is aimed at reducing the primary and secondary adverse outcomes. Anesthesia in robotic surgery varies from anesthesia for open or laparoscopic surgical procedures. The choice of anesthesia influences the perioperative control of pain, nausea, vomiting, and Optic nerve sheath diameter (ONSD). The purpose of this systematic review was to assess outcome variation in patients undergoing transabdominal robot-assisted surgery done under total intravenous anesthesia or inhalational anesthesia. We searched the Cochrane Central Register of Controlled Trials, PubMed, and Google Scholar (January, 2017 to June, 2024). Search terms included "Anesthesia", "Robotics", "prostatectomy", hysterectomy", "nephrectomy", "cholecystectomy" and "cystectomy" with the Boolean operators "AND" and "OR". We searched for randomized controlled trials (RCTs) including adults of both genders aged 18 years and above, who underwent transabdominal robotic-assisted laparoscopic surgery and targeting the consequences related to TIVA or inhalational anesthesia. We reviewed titles and abstracts and proceeded to full-text articles of the eligible studies relevant to inclusion criteria. Mean and standard deviations with 95% CI were calculated. Forest plots were used to present data visually. Six studies (340 patients) were included. We found only one study in which post-operative pain was assessed and results favored intravenous anesthesia in robotic transabdominal surgery. Only two studies reported post-operative nausea and vomiting (PONV). Both studies stated that PONV is reported in few patients in the inhalation anesthesia group. We found evidence suggesting that change in ONSD measurements at 10&#xa0;min after induction (MD 0.04,95% CI -0.02 to 0.11 p&#x2009;=&#x2009;0.19) and 40-60&#xa0;min after Trendelenburg position (MD -0.26, 95% CI -0.34 to 0.17, p&#x2009;=&#x2009;0.16) are much less in intravenous anesthesia group than in inhalation anesthesia group. Total intravenous anesthesia maintains the ONSD and hence the ICP better than inhalational anesthesia in robotic transabdominal surgery with CO2 pneumoperitoneum in Trendelenburg positioning requirements. It would be a safer choice than inhalational anesthesia due to fewer adverse events. This review concludes that TIVA is a better choice than inhalational anesthesia for transabdominal robotic-assisted surgery in urology, gynecology, and gastroenterology in both male and female patients.

Robotic assistance has expanded the scope of minimally invasive major reconstruction in pediatric urology, but adoption varies and comparative advantages over open surgery remain uncertain. ELIGIBILITY CRITERIA: English-language clinical studies reporting primary data on patients <18 years old undergoing the targeted robotic procedures for neurogenic bladder or severe voiding dysfunction. Oncologic indications, editorials, nonclinical studies, and abstracts without full text were excluded. MEDLINE (Ovid), Embase (Embase.com), Cochrane Library (Wiley: CDSR and CENTRAL), and Web of Science Core Collection (Clarivate). A standardized extraction form (with calibration) captured bibliographic details, study design, patient and procedural characteristics, and outcomes (operative time, estimated blood loss, length of stay, pain, complications, continence, reoperation, follow-up). Data were summarized descriptively in tables/figures; no meta-analysis was performed due to heterogeneity of reported data. Of 218 records screened, 66 studies were included from 2004 to 2024. Many were case reports/series. Feasibility reports for catheterizable channels (&#xb1;augmentation/BNR) showed low conversion-to-open (7%), complication rate of 16.7% (most commonly stomal stenosis, wound infection, UTI), mean length of stay 5.7 days, and reported success/continence of &#x223c;99%. Six retrospective comparisons (136 robotic vs 121 open cases) found higher (&#x223c;40%) but similar complication, reoperation, and continence rates between the robotic and open approach. Descriptive trends favoring robotics were lower postoperative morphine equivalents, less estimated blood loss (EBL) and shorter hospital stays. However all studies reported longer robotic operative times. Current literature suggests that robotic major reconstruction in pediatric urology is feasible and safe in experienced hands, with acceptable short and mid-term outcomes in experienced centers. However, long-term functional and overall outcomes remain limited compared to open cohorts. Available comparative studies report broadly similar outcomes, though these findings should be interpreted cautiously given heterogeneity and limited follow up. Adoption of robotic surgery for lower urinary tract reconstruction in children remains constrained by pediatric anatomy, costs, learning curves, and case volume. Standardized definitions of continence, rigorous complication reporting, prospective multicenter data, cost analyses, and long-term functional follow-up are needed to benchmark and optimize care.

Robotic surgery uptake is increasing rapidly, with the anticipation that most laparoscopic procedures will eventually be performed robotically. Multiple benefits have been demonstrated: reduced conversion rates, stoma rates, complications, post-operative pain and length of stay, and improved primary anastomosis rate, oncological outcomes and gastrointestinal recovery. This study aimed to assess the feasibility and outcomes of a full departmental transition to total robotic colorectal practice, in line with the National Health Service robotic surgery strategic vision. This single-centre retrospective cohort study was performed in a UK centre from 2018 to 2024, including the three-year transition period from laparoscopic to total robotic colorectal practice. The primary outcome was conversion rate. Secondary outcomes were post-operative complications, anastomotic leak, stoma rates, resection margins, lymph node harvest, intra-operative blood loss, post-operative pain, return to theatre and length of stay. 1479 operations were analysed: 584 robotic (39.4%), 807 laparoscopic (54.6%) and 88 open (5.9%). 1085 (73.4%) operations were for colorectal cancer, 394 (26.6%) for benign pathologies. All robotic surgery outcomes were non-inferior to laparoscopy. Statistically significant differences were found in conversion rate (2% vs. 12%, p&#x2009;=&#x2009;0.001), intra-operative blood loss (p&#x2009;=&#x2009;0.01), length of stay (4 vs. 5 days, p&#x2009;=&#x2009;0.001), lymph node harvest (21 vs. 20, p&#x2009;=&#x2009;0.006), R0 resection rates ( 90% vs. 87%, p&#x2009;=&#x2009;0.0001) and median PCA volume (38 vs. 67 mls, p&#x2009;=&#x2009;0.001). Full departmental change to total robotic colorectal practice is achievable in both colorectal cancer and benign disease with an improvement upon laparoscopic outcomes.

Robotic liver surgery is rapidly evolving, but its standardization is limited by the lack of dedicated instruments for parenchymal transection. The Harmonic ACE Curved Shears are widely used; however, guidance on optimizing their use and a clear assessment of their advantages and limitations are lacking. This study evaluates the strengths and limitations of this transection method in a newly established robotic hepatopancreatobiliary (HPB) centre, based on surgical outcomes. Patients undergoing robotic liver resection between February and December 2024 were included. Parenchymal transection was performed using a "one-surgeon, fully robotic technique" with the Harmonic ACE Curved Shears. Intraoperative and postoperative data - including operative time, blood loss, clamping time, complications, and hospital stay - were prospectively collected and retrospectively analyzed. Sixteen robotic hepatectomies were performed (15 minor, 1 major) for benign and malignant conditions. Median blood loss was 25 mL (IQR 0-325), mean operative time 341&#xb1;120 minutes, and median clamping time was 8 minutes (IQR 0-56). Fifteen patients had an uneventful postoperative course, with a mean hospital stay of 5.2&#xb1;2.8 days. One patient developed a grade B biliary fistula. No 30-day mortality or readmissions occurred. The fully robotic technique using Harmonic ACE Curved Shears is safe, effective, and reproducible. It replicates the crush-clamp technique and mimics other transection tools, facilitating precise dissection of biliary and vascular structures while minimizing blood loss and bile leaks. This approach may be particularly valuable in newly established robotic HPB centers, helping to achieve satisfactory surgical outcomes even during the early phase of program implementation. Nevertheless, these promising results require confirmation in larger cohorts and further studies, particularly to validate the safety and effectiveness of this technique in major hepatectomies and in procedures of greater complexity.

To expand the performance envelope of current unmanned underwater vehicles (UUVs) operating in near shore environments, researchers have increasingly turned to marine animals as models to develop bio-inspired robotic systems that leverage biological swimming strategies. In particular, California sea lions swim with great maneuverability in highly dynamic flow environments by coordinating multiple, spatially distributed control surfaces along their bodies. Despite significant progress in the development of bio-inspired robots, the individual and combined roles of different control surfaces and how their actuation affects turning of the robotic system remains under explored. In this study, a bio-inspired sea lion robot and its numerical model were used to understand how the actuation angle of control surfaces such as head, pelvis, fore flippers and hind flippers affected pitch and yaw turns. The turning performance of the bio-robotic platform was evaluated using turning radius, maximum angular velocities, and final orientation. Experimental and numerical results showed that actuating anterior control surfaces in combination with posterior control surfaces reduced turning radius and increased maximum angular velocity and final orientation relative to posterior-only actuation. Actuating fore flippers near the center of mass during pitch turns further enhanced turning performance by reducing lateral slip and producing tighter turns. Importantly, the results also revealed that maximum actuation of control surfaces did not always yield superior turning performance, as specific non-maximal head-pelvis actuation combinations produced better turns. These findings demonstrate that turning performance in bio-inspired, multi-body underwater systems depends on both the geometric location of control surfaces and their actuation angles. More broadly, the results suggest that actuation strategies should be tailored to the intended turning behavior, providing design and control guidance for future articulated underwater robots.

This study aimed to evaluate global research trends in robotic surgery in andrology using a bibliometric approach. A comprehensive search was conducted in the Web of Science Core Collection using predefined keywords related to robotic-assisted techniques and andrological procedures. Publications between 2003 and 2025 were included. After applying eligibility criteria, 69 studies (37 articles and 32 reviews) were analyzed. Bibliometric analyses were performed using Biblioshiny and VOSviewer to assess publication output, citation patterns, leading sources, countries, authors, and collaborative networks. The results demonstrated fluctuations in annual scientific production, with the highest number of publications recorded in 2014. Citation trends varied across publication years. Publications were primarily concentrated in leading peer-reviewed journals in the fields of urology, andrology, and robotic surgery, reflecting the specialized and interdisciplinary nature of the field. The United States ranked first in both publication output and citation impact, while Turkey exhibited the highest collaborative strength based on total link strength. Keyword analysis identified vasovasostomy, microsurgery, varicocelectomy, and male infertility as the dominant research themes. Co-authorship and co-citation analyses indicated that the field is shaped by a limited number of influential authors and core studies. In conclusion, robotic surgery in andrology represents a steadily expanding research area characterized by increasing scientific output and evolving collaboration patterns. From a clinical perspective, the concentration of current evidence may limit its generalizability to broader practice. Future multicenter studies evaluating procedure-specific outcomes, functional results, pain relief, complications, long-term durability, and cost-effectiveness may further clarify the role of robotic techniques in andrology.

Artificial sensory systems with synergistic tactile and nociceptive perception are essential for advanced human-robot interaction and environmental monitoring. However, developing scalable, tunable electronic skin (e-skin) that combines ultrasensitive tactile and nociceptive sensing remains challenging. Here, inspired by leaf stomata, we present a suspended biomimetic e-skin enabling 3D deformation-mechanical contact interactions for adjustable sensing. By integrating Langmuir-Blodgett assembly with a mechanical strategy, we achieve large-scale, precise alignment of metal nanowires and controlled crack formation, resulting in ultrahigh sensitivity (205.08 kPa-1) and excellent cyclic stability (120&#x202f;000 cycles). Leveraging its dual-modal sensing mechanism, the e-skin is incorporated into a robotic tactile system, enabling non-destructive grasping of soft objects and real-time avoidance of sharp objects under closed-loop control. This simple, scalable approach provides a versatile platform for ultrasensitive, adaptive e-skin, advancing robotic tactile and nociceptive perception and promoting intelligent human-robot interaction.

Few studies have examined the acceptance of transfer-care robots across diverse caregiver roles and practice settings, with most research limited to single professional groups or institutional environments. This mixed-methods study integrates nurses, personal care assistants, and family caregivers from hospitals, long-term care facilities, and home care to capture a holistic perspective on technology adoption across the continuum of care. Employing a sequential explanatory design guided by Davis' Technology Acceptance Model, we conducted a quantitative survey (n=224) followed by focus group interviews (n=15). Quantitative findings revealed that job relevance was the strongest predictor of intention to use (&#x3b2;=0.50, P<.001), with perceived usefulness and self-efficacy also being significant (adj. R&#xb2;=.81). Thematic analysis identified 4 themes-physical burden of transfers, urgent need for robotic assistance, desire for safe and efficient robots, and aspirations for transformative technology-which contextualized these predictors by highlighting how TCRs can mitigate physical strain and fall risks. The findings highlight the necessity of informatics strategies prioritizing user-centered design and workflow alignment. These results can inform efforts to enhance caregiving environments and support the framework for successful implementation of robotic assistance in diverse health care settings.

Sleeve lobectomy with bronchoplasty is a complex yet lung-sparing procedure traditionally performed via open thoracotomy. Robotic-assisted thoracoscopic surgery, with enhanced visualization and instrument dexterity, may facilitate this technically demanding procedure in a minimally invasive setting. We report the case of an 85-year-old man with adenocarcinoma in the right upper lobe, accompanied by an isolated intrapulmonary metastasis and an enlarged lymph node #4R and #11s, with #11s invading the orifice of the right upper lobe bronchus. The clinical stage was cT3N2aM0 (stage IIIB). Because of bronchial involvement by metastatic lymph node #11s, robotic right upper sleeve lobectomy with bronchoplasty was performed. A five-port approach was used. The right upper lobe pulmonary vessels were individually dissected and divided using robotic staplers. After sleeve resection of the bronchus, bronchial reconstruction was completed with a continuous barbed suture. The anastomosis was reinforced with a free pericardial fat pad and fibrin sealant. Console time was 226 minutes, with minimal blood loss. The chest tube was removed on postoperative Day 1, and the patient was discharged on postoperative Day 5 without complications. Pathology confirmed pT3N2bM0 adenocarcinoma with negative margins. Robotic right upper sleeve lobectomy with bronchoplasty may be a feasible minimally invasive option in selected patients requiring complex airway reconstruction.

Sleeve lobectomy with bronchoplasty is a complex but lung-preserving operation, often requiring open thoracotomy. Robotic-assisted thoracoscopic surgery offers enhanced visualization and instrument dexterity, enabling such procedures to be performed with minimal invasiveness. We report a case of a 75-year-old man with squamous cell carcinoma located in the lingual segment of the left upper lobe, which invaded to the entrance of left upper lobe bronchus. The tumour was staged as cT2aN0M0. Due to its central location, robotic left upper sleeve lobectomy with bronchoplasty was selected. A five-port approach was used. Pulmonary vessels of the left upper lobe were dissected and divided using robotic staplers. After sleeve resection of the bronchus, bronchial reconstruction was performed using a continuous barbed suture, and the anastomosis was reinforced with a pericardial fat pad and fibrin sealant. The console time was 267 minutes with minimal blood loss. The chest tube was removed on postoperative Day 1, and the patient was discharged on Day 5 without complications. Pathology confirmed pT2aN0M0 squamous cell carcinoma with negative margins. Robotic left upper sleeve lobectomy with bronchoplasty is feasible and safe in selected patients, providing the advantages of minimally invasive surgery without compromising oncological outcomes.

We explore an approach to develop telemedical Graphical User Interfaces (GUIs) using User-centered Design (UCD) methods. In contrast with prior work that emphasizes system integration, we center on the GUI as the clinician's primary interface. In a user-centered, two-stage process, we developed a modular and generalized GUI architecture and adapted it to a Robotic Ultrasound System (RUSS) and a robotic Tension Pneumothorax (tPTX) system. The GUIs were iteratively co-designed and evaluated with physicians using mixed methods (System Usability Scale (SUS), end-user-adapted heuristics, eye-tracking). The results of the study confirm the benefits of UCD methods for the development of GUIs for telemedical robotic systems. Repeated exposure increased efficiency across tasks and scenarios, indicating the usability (training effect) and consistency (cross-scenario learning transfer) of a modular GUI architecture. The mixed-methods design provided complementary insights via triangulation, helped to analyze outliers, and revealed additional design issues not captured by one method alone. A user-centered GUI development process with multiple evaluation rounds can improve the usability of telemedical robotic systems for medical professionals. Our findings show that a modular architecture can facilitate the transfer of training effects across implementations and clinical use cases by preserving high-level structures and interaction concepts.

Robot-assisted minimally invasive surgery offers high precision and dexterity, opening up new possibilities for intraoperative imaging to improve tumor localization. B-mode ultrasound provides real-time anatomical views, while strain elastography (SE) adds tissue stiffness information. Used together, they provide complementary cues that help increase the accuracy of tumor localization by improving boundary detection. We present a robotics-integrated framework for autonomous ultrasound scanning and multimodal tumor segmentation. The system utilizes the da Vinci&#xae; Classic surgical robot with the da Vinci&#xae; Research Kit (dVRK) and a custom ultrasound transducer. It simultaneously acquires paired B-mode and SE images from silicone phantoms and ex vivo porcine livers. Our architecture extends the conventional U-Net by integrating dual encoders with cross-attention and selective fusion. Cross-attention allows one modality to refine the features of the other, while selective fusion balances their contributions. We performed experiments on a multimodal dataset to validate the effectiveness of the proposed method. Results indicate that our approach outperforms unimodal baselines and standard fusion methods across both segmentation and classification metrics. These findings suggest that multimodal cross-attention and selective fusion can improve tumor segmentation in ultrasound imaging. Ultimately, the goal is to use such advances to support intraoperative guidance for robot-assisted liver surgery.

Robotic-assisted thoracic surgery has become increasingly utilized for the management of lung cancer, particularly in technically demanding anatomical resections. The robotic platform provides enhanced depth perception, refined instrument articulation and improved precision. This facilitates complex pulmonary resections such as segmentectomies. This minimally invasive approach is increasingly favoured over open thoracotomy due to its association with reduced postoperative complications and accelerated recovery. Anatomical segmentectomy remains technically challenging due to variations in bronchovascular anatomy. The incorporation of three-dimensional reconstruction imaging enables detailed pre-operative assessment of tumour location and its relationship to surrounding structures, allowing for more precise and individualized surgical planning. Despite these advantages, the routine use of three-dimensional imaging in thoracic surgery is not yet widely established across thoracic surgery centres, and has limited exposure in the literature. This video atlas series presents a robotic-assisted anatomical segmentectomy guided by three-dimensional reconstruction. This tutorial provides a structured, step-by-step approach to performing a right S2 posterior segmentectomy for a patient with a right upper lobe tumour.

Nontechnical skills (NTS), such as communication, leadership, and situational awareness, are essential for ensuring surgical safety. However, they are often prioritized less than technical skills. This narrative review summarizes recent technological progress in teaching and evaluating NTS in urology, emphasising the use of simulation, robotic-specific frameworks, and artificial intelligence. Validated assessment tools such as NoTSUS and ICARS have been developed to provide objective measures of NTS, particularly to address communication difficulties in the robotic console setting. Recent research indicates that technical seniority does not necessarily correlate with NTS mastery, but the use of distributed and hybrid simulation significantly enhances trainee outcomes. Additionally, the adoption of large language models (LLMs) and machine learning is enabling automated tone and emotion analysis, giving trainees detailed, unbiased feedback. New virtual patient platforms like SimConverse and SimURO provide affordable and psychologically safe environments for repeated NTS practice. The rapid advancement in urological surgery, marked by increasing use of robotics and greater physical separation from patients, calls for a structured approach to NTS training. Breakthroughs in AI and immersive simulation are shifting NTS from a vague 'soft skill' to a concrete, data-driven, measurable skill. To achieve the best patient results, these digital technologies should be deliberately incorporated into urological education as vital additions to standard technical instruction and mentorship.

To report perioperative and short-term outcomes of single-port (SP) robotic vascular-preserving (non-transecting) Y-V flap pyeloplasty with stricturoplasty for ureteropelvic junction obstruction (UPJO). The most commonly performed pyeloplasty technique is the dismembered Anderson-Hynes technique; however, transection of the ureter compromises its blood supply and makes revision surgery more complex. Non-transecting pyeloplasty preserves the longitudinal ureteral blood supply and serves as an alternative to transecting techniques. All patients who underwent SP robotic-assisted non-transecting Y-V flap pyeloplasty with stricturoplasty for primary UPJO between December 2020 and December 2024 were retrospectively reviewed. Surgical success was defined as the absence of secondary intervention (endoscopic or surgical), resolution or improvement of symptoms, and stable or improved postoperative imaging findings. A total of 21 cases met the inclusion criteria. Median operative time was 109&#xa0;min. Median follow-up was 73 weeks. Overall surgical success was achieved in 95% of patients. There were no intraoperative complications, and the median estimated blood loss was 15 mL. Most patients were discharged the same day (18/21, 86%), with no Clavien-Dindo grade&#x2009;&#x2265;&#x2009;III complications. Postoperative renal scintigraphy was obtained in 8 patients, all of whom demonstrated improved drainage (T&#xbd; <20&#xa0;min). The remaining patients were followed with clinical assessment and postoperative imaging. One patient developed recurrent obstruction after stent removal and was successfully managed with secondary endopyelotomy. SP robotic non-transecting Y-V flap pyeloplasty with stricturoplasty appears feasible and safe in selected patients with primary UPJO, with favorable short-term outcomes in this single-surgeon retrospective series. Further study with standardized functional follow-up is needed to define durability and appropriate patient selection.