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Bereuter JP, Geissler ME, Geissler R, Schmidt S, Buck N, Weiß J, Fries A, Krause-Jüttler G, Weitz J, Distler M, Presslein K, Oehme F, von Bechtolsheim F. Impact of Operative Room Noise on Laparoscopic Performance - A Prospective, Randomized Crossover Trial. J Surg Res 2024; 302:648-655. [PMID: 39197287 DOI: 10.1016/j.jss.2024.07.110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Revised: 07/01/2024] [Accepted: 07/29/2024] [Indexed: 09/01/2024]
Abstract
INTRODUCTION Surgeons are often exposed to different types of operative room (OR) noise, for instance machine alarms, phone calls, and interacting objects. The aim of this study was to evaluate the effect of OR noise on the surgeons' laparoscopic performance. METHODS A total of 30 laparoscopic novices participated in this single-center, prospective, randomized cross-over trial after completing a standardized laparoscopic training until reaching proficiency. Afterward, all participants performed four different laparoscopic tasks (peg transfer, circle cutting, balloon resection, suture, and knot) twice, once under noise exposure (intervention group), and once without any noise (control group). Primary endpoints were the force exertion and motion analyses. To assess the psychological workload the NASA task load index score was used. RESULTS The error rates varied and were significantly different between the noise and the control group. More complex tasks like the circle cutting and suture and knot task revealed higher error rates concerning precision (circle cutting: P < 0.01; suture and knot: P < 0.01). In line with increased error rates in the circle cutting task, increased NASA task load index scores were observed in this task (P = 0.03). However, no significant differences were found in force parameters, such as the maximal force exertion (peg transfer: P = 0.43; circle cutting: P = 0.54; balloon resection: P = 0.64; suture and knot: P = 0.63) and the mean force exertion (peg transfer: P = 0.43; circle cutting: P = 0.54; balloon resection: P = 0.64; suture and knot: P = 0.63) between the groups. CONCLUSIONS Exposure to normal OR noise led to higher error rates in two of four tasks. This effect could be linked to an increased psychological workload that was present under normal OR noise exposure. However, normal OR noise does not appear to impact surgical novices' laparoscopic task performance regarding applied forces and instrument motion.
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Affiliation(s)
- Jean-Paul Bereuter
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Mark Enrik Geissler
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Rona Geissler
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Sofia Schmidt
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Nathalie Buck
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Juliane Weiß
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Alexa Fries
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Grit Krause-Jüttler
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany; Centre for Tactile Internet with Human-in-the-Loop (CeTI), TUD Dresden University of Technology, Dresden, Germany
| | - Jürgen Weitz
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Marius Distler
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany; Centre for Tactile Internet with Human-in-the-Loop (CeTI), TUD Dresden University of Technology, Dresden, Germany
| | - Kristof Presslein
- Faculty of Medicine, Carus Lehrzentrum (CarL), TUD Dresden University of Technology, Dresden, Germany
| | - Florian Oehme
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany
| | - Felix von Bechtolsheim
- Department of Visceral, Thoracic and Vascular Surgery, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Dresden, Germany; Centre for Tactile Internet with Human-in-the-Loop (CeTI), TUD Dresden University of Technology, Dresden, Germany.
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Boal MWE, Anastasiou D, Tesfai F, Ghamrawi W, Mazomenos E, Curtis N, Collins JW, Sridhar A, Kelly J, Stoyanov D, Francis NK. Evaluation of objective tools and artificial intelligence in robotic surgery technical skills assessment: a systematic review. Br J Surg 2024; 111:znad331. [PMID: 37951600 PMCID: PMC10771126 DOI: 10.1093/bjs/znad331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 09/18/2023] [Accepted: 09/19/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND There is a need to standardize training in robotic surgery, including objective assessment for accreditation. This systematic review aimed to identify objective tools for technical skills assessment, providing evaluation statuses to guide research and inform implementation into training curricula. METHODS A systematic literature search was conducted in accordance with the PRISMA guidelines. Ovid Embase/Medline, PubMed and Web of Science were searched. Inclusion criterion: robotic surgery technical skills tools. Exclusion criteria: non-technical, laparoscopy or open skills only. Manual tools and automated performance metrics (APMs) were analysed using Messick's concept of validity and the Oxford Centre of Evidence-Based Medicine (OCEBM) Levels of Evidence and Recommendation (LoR). A bespoke tool analysed artificial intelligence (AI) studies. The Modified Downs-Black checklist was used to assess risk of bias. RESULTS Two hundred and forty-seven studies were analysed, identifying: 8 global rating scales, 26 procedure-/task-specific tools, 3 main error-based methods, 10 simulators, 28 studies analysing APMs and 53 AI studies. Global Evaluative Assessment of Robotic Skills and the da Vinci Skills Simulator were the most evaluated tools at LoR 1 (OCEBM). Three procedure-specific tools, 3 error-based methods and 1 non-simulator APMs reached LoR 2. AI models estimated outcomes (skill or clinical), demonstrating superior accuracy rates in the laboratory with 60 per cent of methods reporting accuracies over 90 per cent, compared to real surgery ranging from 67 to 100 per cent. CONCLUSIONS Manual and automated assessment tools for robotic surgery are not well validated and require further evaluation before use in accreditation processes.PROSPERO: registration ID CRD42022304901.
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Affiliation(s)
- Matthew W E Boal
- The Griffin Institute, Northwick Park & St Marks’ Hospital, London, UK
- Wellcome/ESPRC Centre for Interventional Surgical Sciences (WEISS), University College London (UCL), London, UK
- Division of Surgery and Interventional Science, Research Department of Targeted Intervention, UCL, London, UK
| | - Dimitrios Anastasiou
- Wellcome/ESPRC Centre for Interventional Surgical Sciences (WEISS), University College London (UCL), London, UK
- Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Freweini Tesfai
- The Griffin Institute, Northwick Park & St Marks’ Hospital, London, UK
- Wellcome/ESPRC Centre for Interventional Surgical Sciences (WEISS), University College London (UCL), London, UK
| | - Walaa Ghamrawi
- The Griffin Institute, Northwick Park & St Marks’ Hospital, London, UK
| | - Evangelos Mazomenos
- Wellcome/ESPRC Centre for Interventional Surgical Sciences (WEISS), University College London (UCL), London, UK
- Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Nathan Curtis
- Department of General Surgey, Dorset County Hospital NHS Foundation Trust, Dorchester, UK
| | - Justin W Collins
- Division of Surgery and Interventional Science, Research Department of Targeted Intervention, UCL, London, UK
- University College London Hospitals NHS Foundation Trust, London, UK
| | - Ashwin Sridhar
- Division of Surgery and Interventional Science, Research Department of Targeted Intervention, UCL, London, UK
- University College London Hospitals NHS Foundation Trust, London, UK
| | - John Kelly
- Division of Surgery and Interventional Science, Research Department of Targeted Intervention, UCL, London, UK
- University College London Hospitals NHS Foundation Trust, London, UK
| | - Danail Stoyanov
- Wellcome/ESPRC Centre for Interventional Surgical Sciences (WEISS), University College London (UCL), London, UK
- Computer Science, UCL, London, UK
| | - Nader K Francis
- The Griffin Institute, Northwick Park & St Marks’ Hospital, London, UK
- Division of Surgery and Interventional Science, Research Department of Targeted Intervention, UCL, London, UK
- Yeovil District Hospital, Somerset Foundation NHS Trust, Yeovil, Somerset, UK
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Singh R, Godiyal AK, Chavakula P, Suri A. Craniotomy Simulator with Force Myography and Machine Learning-Based Skills Assessment. Bioengineering (Basel) 2023; 10:bioengineering10040465. [PMID: 37106652 PMCID: PMC10136274 DOI: 10.3390/bioengineering10040465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 02/24/2023] [Accepted: 02/26/2023] [Indexed: 04/29/2023] Open
Abstract
Craniotomy is a fundamental component of neurosurgery that involves the removal of the skull bone flap. Simulation-based training of craniotomy is an efficient method to develop competent skills outside the operating room. Traditionally, an expert surgeon evaluates the surgical skills using rating scales, but this method is subjective, time-consuming, and tedious. Accordingly, the objective of the present study was to develop an anatomically accurate craniotomy simulator with realistic haptic feedback and objective evaluation of surgical skills. A CT scan segmentation-based craniotomy simulator with two bone flaps for drilling task was developed using 3D printed bone matrix material. Force myography (FMG) and machine learning were used to automatically evaluate the surgical skills. Twenty-two neurosurgeons participated in this study, including novices (n = 8), intermediates (n = 8), and experts (n = 6), and they performed the defined drilling experiments. They provided feedback on the effectiveness of the simulator using a Likert scale questionnaire on a scale ranging from 1 to 10. The data acquired from the FMG band was used to classify the surgical expertise into novice, intermediate and expert categories. The study employed naïve Bayes, linear discriminant (LDA), support vector machine (SVM), and decision tree (DT) classifiers with leave one out cross-validation. The neurosurgeons' feedback indicates that the developed simulator was found to be an effective tool to hone drilling skills. In addition, the bone matrix material provided good value in terms of haptic feedback (average score 7.1). For FMG-data-based skills evaluation, we achieved maximum accuracy using the naïve Bayes classifier (90.0 ± 14.8%). DT had a classification accuracy of 86.22 ± 20.8%, LDA had an accuracy of 81.9 ± 23.6%, and SVM had an accuracy of 76.7 ± 32.9%. The findings of this study indicate that materials with comparable biomechanical properties to those of real tissues are more effective for surgical simulation. In addition, force myography and machine learning provide objective and automated assessment of surgical drilling skills.
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Affiliation(s)
- Ramandeep Singh
- Neuro-Engineering Lab, Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Anoop Kant Godiyal
- Department of Physical Medicine and Rehabilitation, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Parikshith Chavakula
- Neuro-Engineering Lab, Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Ashish Suri
- Neuro-Engineering Lab, Department of Neurosurgery, All India Institute of Medical Sciences, New Delhi 110029, India
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Kao HY, Yang YC, Hung YH, Wu YJ. When Does Da Vanci Robotic Surgical Systems Come Into Play? Front Public Health 2022; 10:828542. [PMID: 35174126 PMCID: PMC8841676 DOI: 10.3389/fpubh.2022.828542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 01/06/2022] [Indexed: 12/04/2022] Open
Abstract
The emergent of medical science and technology has risen the minimally invasive surgery. Da Vinci Robotic Surgical Systems (RSS) is the trend at present. Compared with the past surgical methods, many studies related to RSS tend to explore postoperative outcomes and quality of life or compare the advantages and disadvantages than the other surgery. Few studies to understand the patients' willing who use RSS. This study mainly explores the patients' willingness and adopts the Technology Acceptance Model (TAM) as the theoretical foundation, and appended the trust concept to discuss. The study was a retrospective study and used a structured questionnaire to conduct a survey. The subjects included the patients with single-disease who had used RSS in a Medical Center of Southern Taiwan but excluded the patients with multiple disorder. This study conducted SPSS 22.0 and Smart PLS 2.0 software for statistical analysis, which included descriptive statistical analysis and applied Partial Least Squares (PLS) analysis to test the research model and to examine the established hypotheses. A total of 136 cases were collected in this study. Study validation was tested. Trust positively affects Perceived Usefulness (β = 0.550) and Perceived Ease of Use (β = 0.300). Perceived Ease of Use positively affects Perceived Usefulness (β = 0.188). Perceived Usefulness positively affects Attitude Toward Using (β = 0.589. Attitude Toward Using positively affects Behavioral Intention (β = 0.446. The relationship between perceived Ease of Use and Attitude toward Using was insignificant. Additionally, the relationship between Perceived Usefulness and Behavioral Intention was insignificant. In the research results, we found that patients are mostly in the middle and high age groups, and if the patient himself feels that RSS is extremely helpful to his illness, the intensity of his choice of intention will be high. In comparison, the information related to RSS has been clearly known, it does not directly affect the selection intention. According to age, most of the choices of RSS is based on safety and risk considerations, and it is beneficial to the patient himself, but RSS is also more expensive. We recommended that the government consider ββ reimbursing the RSS process in health insurance programs to meet the needs and expectations of patients.
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Affiliation(s)
- Hao-Yun Kao
- Department of Healthcare Administration and Medical Informatics, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Yi-Chen Yang
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Yu-Han Hung
- Department of Healthcare Administration and Medical Informatics, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan
- Department of Nursing, Yuan's General Hospital, Kaohsiung, Taiwan
- Yu-Han Hung
| | - Yenchun Jim Wu
- College of Humanities and Arts, National Taipei University of Education, Taipei, Taiwan
- Graduate Institute of Global Business and Strategy, National Taiwan Normal University, Taipei, Taiwan
- *Correspondence: Yenchun Jim Wu
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Zhang N, Yan P, Feng L, Chu X, Li J, Li J, Guo K, Guo T, Liu X, Yang K. Top 100 most-cited original articles, systematic reviews/meta-analyses in robotic surgery: A scientometric study. Asian J Surg 2021; 45:8-14. [PMID: 33895050 DOI: 10.1016/j.asjsur.2021.04.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 02/11/2021] [Accepted: 04/05/2021] [Indexed: 12/21/2022] Open
Abstract
The aim of this study was to explore and analyze the main features of the top 100 most-cited original articles, systematic reviews (SRs)/meta-analyses (MAs) in the field of robotic surgery, through scientometric analysis. VOSviewer and Excel 2019 were employed to conduct this scientometric study. We found that the majority of original articles (72/100) were published during the 2000s, while the majority of the top 100 most-cited SRs/MAs (91/100) during the 2010s. The USA was the most dominant country (n = 78), Henry Ford Health System was the most productive institution (n = 10), and Menon M was the largest contributing first author (n = 5) of the top 100 most-cited original articles. The USA was the most dominant country (n = 33), University of Padua was the most productive institution (n = 9), and Ficarra V was the largest contributing first author (n = 4) of the top 100 most-cited SRs/MAs. The top 100 most-cited original articles in robotic surgery have focused on the feasibility, outcomes and learning curve of robotic surgery for various neoplasms and cancers. The top 100 most-cited SRs/MAs have focused on the differences between robotic surgery and other types of surgery, with respect to the learning curve, costs, outcomes and experience in treating neoplasms, cancer and other diseases. In the future, the formation of cross-institutional and cross-disciplinary cooperation teams should be promoted and corresponding regulations and standards for specific diseases should be developed to regulate and promote the development of robotic surgery.
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Affiliation(s)
- Na Zhang
- Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, 730000, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, 730000, China
| | - Peijing Yan
- Department of Epidemiology and Health Statistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, 610044, China
| | - Lufang Feng
- Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, 730000, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, 730000, China
| | - Xiajing Chu
- Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, 730000, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, 730000, China
| | - Jingwen Li
- Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, 730000, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, 730000, China
| | - Jieyun Li
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, 730000, China
| | - Kangle Guo
- Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, 730000, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, 730000, China
| | - Tiankang Guo
- General Surgery Clinical Medical Center, Gansu Provincial Hospital, Lanzhou, 730000, China
| | - Xingrong Liu
- Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, 730000, China.
| | - Kehu Yang
- Evidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, 730000, China; Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China; Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, 730000, China.
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Mcleod RWJ, Myint-Wilks L, Davies SE, Elhassan HA. The impact of noise in the operating theatre: a review of the evidence. Ann R Coll Surg Engl 2021; 103:83-87. [PMID: 33559553 PMCID: PMC9773860 DOI: 10.1308/rcsann.2020.7001] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
INTRODUCTION Noise has been recognised to have a negative impact on performance and wellbeing in many settings. Average noise levels have been found to range between 51dB and 79dB in operating theatres. Despite these levels of noise, there is little research investigating their effect on surgical team functioning. METHODS A literature review to look at the impact of noise in the operating theatre was performed on MEDLINE, which included the search terms 'noise' OR 'distraction' AND 'technical skill' OR 'Surgical skill' OR 'Operating Room'. Only 10 of 307 articles identified were deemed relevant. FINDINGS Eight of ten studies found noise to be detrimental to communication and surgical performance, particularly regarding total errors and time to task completion. No studies found noise to be beneficial. Two studies found case-irrelevant verbal communication to be a frequent form of noise pollution in operating theatres; this is both perceived by surgeons to be distracting and delays patient care. CONCLUSION Noise and irrelevant verbal communications were both found to be harmful to surgical performance, surgeon experience and team functioning.
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Affiliation(s)
- RWJ Mcleod
- University Hospital of Wales, Cardiff, UK
| | | | - SE Davies
- University Hospital of Wales, Cardiff, UK
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AORN
Position Statement on Managing Distractions and Noise During Perioperative Patient Care. AORN J 2020. [DOI: 10.1002/aorn.13064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Weber J, Catchpole K, Becker AJ, Schlenker B, Weigl M. Effects of Flow Disruptions on Mental Workload and Surgical Performance in Robotic-Assisted Surgery. World J Surg 2018; 42:3599-3607. [PMID: 29845381 DOI: 10.1007/s00268-018-4689-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
BACKGROUND Robotic systems introduced new surgical and technical demands. Surgical flow disruptions are critical for maintaining operating room (OR) teamwork and patient safety. Specifically for robotic surgery, effects of intra-operative disruptive events for OR professionals' workload, stress, and performance have not been investigated yet. This study aimed to identify flow disruptions and assess their association with mental workload and performance during robotic-assisted surgery. METHODS Structured expert-observations to identify different disruption types during 40 robotic-assisted radical prostatectomies were conducted. Additionally, 216 postoperative reports on mental workload (mental demands, situational stress, and distractions) and performance of all OR professionals were collected. RESULTS On average 15.8 flow disruptions per hour were observed with the highest rate after abdominal insufflation and before console time. People entering the OR caused most flow disruptions. Disruptions due to equipment showed the highest severity of interruption. Workload significantly correlated with severity of disruptions due to coordination and communication. CONCLUSIONS Flow disruptions occur frequently and are associated with increased workload. Therefore, strategies are needed to manage disruptions to maintain OR teamwork and safety during robotic-assisted surgery.
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Affiliation(s)
- Jeannette Weber
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-University Munich, Munich, Germany.
- Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany.
- Institute of Occupational, Social and Environmental Medicine, Centre for Health and Society, Heinrich-Heine-University Düsseldorf, Universitätsstraße 1, 40225, Düsseldorf, Germany.
| | - Ken Catchpole
- Department of Anesthesia and Perioperative Medicine, Medical University of South Carolina, Charleston, USA
| | - Armin J Becker
- Department of Urology, University Hospital Grosshadern, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Boris Schlenker
- Department of Urology, University Hospital Grosshadern, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Matthias Weigl
- Institute and Outpatient Clinic for Occupational, Social and Environmental Medicine, Ludwig-Maximilians-University Munich, Munich, Germany
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Fan G, Zhou Z, Zhang H, Gu X, Gu G, Guan X, Fan Y, He S. Global scientific production of robotic surgery in medicine: A 20-year survey of research activities. Int J Surg 2016; 30:126-31. [PMID: 27154617 DOI: 10.1016/j.ijsu.2016.04.048] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2016] [Revised: 04/24/2016] [Accepted: 04/28/2016] [Indexed: 10/21/2022]
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