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Background: Robotic platforms have the potential advantage of providing additional dexterity and precision to surgeons while performing complex laparoscopic tasks, especially for those in training. Few quantitative evaluations of surgical task performance comparing laparoscopic and robotic platforms among surgeons of varying experience levels have been done. We compared measures of quality and efficiency of Fundamentals of Laparoscopic Surgery task performance on these platforms in novices and experienced laparoscopic and robotic surgeons.
Methods: Fourteen novices, 12 expert laparoscopic surgeons (>100 laparoscopic procedures performed, no robotics experience), and five expert robotic surgeons (>25 robotic procedures performed) performed three Fundamentals of Laparoscopic Surgery tasks on both laparoscopic and robotic platforms: peg transfer (PT), pattern cutting (PC), and intracorporeal suturing. All tasks were repeated three times by each subject on each platform in a randomized order. Mean completion times and mean errors per trial (EPT) were calculated for each task on both platforms. Results were compared using Student's t-test (P < 0.05 considered statistically significant).
Results: Among novices, greater errors were noted during laparoscopic PC (Lap 2.21 versus Robot 0.88 EPT, P < 0.001). Among expert laparoscopists, greater errors were noted during laparoscopic PT compared with robotic (PT: Lap 0.14 versus Robot 0.00 EPT, P = 0.04). Among expert robotic surgeons, greater errors were noted during laparoscopic PC compared with robotic (Lap 0.80 versus Robot 0.13 EPT, P = 0.02). Among expert laparoscopists, task performance was slower on the robotic platform compared with laparoscopy. In comparisons of expert laparoscopists performing tasks on the laparoscopic platform and expert robotic surgeons performing tasks on the robotic platform, expert robotic surgeons demonstrated fewer errors during the PC task (P = 0.009).
Conclusions: Robotic assistance provided a reduction in errors at all experience levels for some laparoscopic tasks, but no benefit in the speed of task performance. Robotic assistance may provide some benefit in precision of surgical task performance.
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http://dx.doi.org/10.1016/j.jss.2017.07.037 | DOI Listing |
Evol Comput
September 2025
Computer Science Department, Tel-Hai College, and The Galilee Research Institute - Migal, Upper Galilee, Israel
Mixed-integer (MI) quadratic models subject to quadratic constraints, known as All- Quadratic MI Programs, constitute a challenging class of NP-complete optimization problems. The particular scenario of unbounded integers defines a subclass that holds the distinction of being even undecidable. This complexity suggests a possible soft-spot for Mathematical Programming (MP) techniques, which otherwise constitute a good choice to treat MI problems.
View Article and Find Full Text PDFJMIR Hum Factors
September 2025
Villa Beretta Rehabilitation Center, Costa Masnaga, Italy.
Background: Telerehabilitation is a promising solution to provide continuity of care. Most existing telerehabilitation platforms focus on rehabilitating upper limbs, balance, and cognitive training, but exercises improving cardiovascular fitness are often neglected.
Objective: The objective of this study is to evaluate the acceptability and feasibility of a telerehabilitation intervention combining cognitive and aerobic exercises.
PLoS One
September 2025
Department of Smart Manufacturing, Industrial Perception and Intelligent Manufacturing Equipment Engineering Research Center of Jiangsu Province, Nanjing Vocational University of Industry Technology, Nanjing, Jiangsu, China.
In the field of quality control, metal surface defect detection is an important yet challenging task. Although YOLO models perform well in most object detection scenarios, metal surface images under operational conditions often exhibit coexisting high-frequency noise components and spectral aliasing background textures, and defect targets typically exhibit characteristics such as small scale, weak contrast, and multi-class coexistence, posing challenges for automatic defect detection systems. To address this, we introduce concepts including wavelet decomposition, cross-attention, and U-shaped dilated convolution into the YOLO framework, proposing the YOLOv11-WBD model to enhance feature representation capability and semantic mining effectiveness.
View Article and Find Full Text PDFPLoS One
September 2025
Seidenberg School of Computer Science and Information Systems, Pace University, New York, New York, United States of America.
While there has been extensive research on techniques for explainable artificial intelligence (XAI) to enhance AI recommendations, the metacognitive processes in interacting with AI explanations remain underexplored. This study examines how AI explanations impact human decision-making by leveraging cognitive mechanisms that evaluate the accuracy of AI recommendations. We conducted a large-scale experiment (N = 4,302) on Amazon Mechanical Turk (AMT), where participants classified radiology reports as normal or abnormal.
View Article and Find Full Text PDFCereb Cortex
August 2025
School of Psychology, University of Surrey, Stag Hill, Guildford, Surrey, GU2 7XH, United Kingdom.
Alpha oscillations have been implicated in the maintenance of working memory representations. Notably, when memorised content is spatially lateralised, the power of posterior alpha activity exhibits corresponding lateralisation during the retention interval, consistent with the retinotopic organisation of the visual cortex. Beyond power, alpha frequency has also been linked to memory performan ce, with faster alpha rhythms associated with enhanced retention.
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