OBJECTIVE: To develop a decision-making program and analyze multi-institutional outcomes of RAC-IVCT versus RAT-IVCT.
DESIGN, SETTING, AND PARTICIPANTS: Ninety patients with renal cell carcinoma (RCC) with level II IVCT were included from eight Chinese urological centers, and underwent RAC-IVCT (30 patients) or RAT-IVCT (60 patients) from June 2013 to January 2019.
SURGICAL PROCEDURE: The surgical strategy was based on IVCT imaging characteristics. RAT-IVCT was performed with standardized cavotomy, thrombectomy, and IVC reconstruction. RAC-IVCT was mainly performed in patients with extensive IVC wall invasion when the collateral blood vessels were well-established. For right-sided RCC, the IVC from the infrarenal vein to the infrahepatic veins was stapled. For left-sided RCC, the IVC from the suprarenal vein to the infrahepatic veins was removed and caudal IVC reconstruction was performed to ensure the right renal vein returned through the IVC collaterals.
MEASUREMENTS: Clinicopathological, operative, and survival outcomes were collected and analyzed.
RESULTS AND LIMITATIONS: All procedures were successfully performed without open conversion. The median operation time (268 vs 190 min) and estimated blood loss (1500 vs 400 ml) were significantly greater for RAC-IVCT versus RAT-IVCT (both p < 0.001). IVC invasion was a risk factor for progression-free and overall survival at midterm follow-up. Large-volume and long-term follow-up studies are needed.
CONCLUSIONS: RAC-IVCT or RAT-IVCT represents an alternative minimally invasive approach for selected RCC patients with level II IVCT. Selection of RAC-IVCT or RAT-IVCT is mainly based on preoperative IVCT imaging characteristics, including the presence of IVC wall invasion, the affected kidney, and establishment of the collateral circulation.
PATIENT SUMMARY: In this study we found that robotic surgeries for level II inferior vena cava thrombus were feasible and safe. Preoperative imaging played an important role in establishing an appropriate surgical plan.
METHODS: We prospectively reviewed HRQOL parameters using Short-Form Health Survey, patient self-reporting of urinary incontinence and International Index of Erectile Function, among patients who underwent RARP between 2010 and 2016.
RESULTS: Among 249 men studied, all had significantly worse HRQOL domain scores at 1 month post operatively but 24 months after surgery, all domains reached or surpassed their baseline values. Only Bodily Pain, General Health, Role-Emotional, Mental Health domains, and Mental Health Composite were significantly improved. Improvement in urinary continence was mirrored by improvements in both Mental and Physical Component Scores.
CONCLUSIONS: Within a 2-year post-operative period, men who underwent RARP had regained their overall quality of life. The recovery of urinary continence significantly impacted the mental, physical, emotional, and social well-being of those patients.
OBJECTIVES: This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.
RESULTS: The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.
CONCLUSION: The results are compared with the existing method for metrics accuracy, classification time, and recall.
OBJECTIVES: In this manuscript, the Robotic Facial Recognition System using the Compound Classifier (RERS-CC) is introduced to improve the recognition rate of human faces. The process is differentiated into classification, detection, and recognition phases that employ principal component analysis based learning. In this learning process, the errors in image processing based on the extracted different features are used for error classification and accuracy improvements.
RESULTS: The performance of the proposed RERS-CC is validated experimentally using the input image dataset in MATLAB tool. The performance results show that the proposed method improves detection and recognition accuracy with fewer errors and processing time.
CONCLUSION: The input image is processed with the knowledge of the features and errors that are observed with different orientations and time instances. With the help of matching dataset and the similarity index verification, the proposed method identifies precise human face with augmented true positives and recognition rate.
OBJECTIVES: This paper discusses RISAPI of our original work in the field, which shows how probabilistic planning and system theory algorithms in workplace robotic systems that work with people can allow for that reasoning using a security robot system. The problem is a general way as an incomplete knowledge 2-player game.
RESULTS: In this general framework, the various hypotheses and these contribute to thrilling and complex robot behavior through real-time interaction, which transforms actual human subjects into a spectrum of production systems, robots, and care facilities.
CONCLUSION: The models of the internal human situation, in which robots can be designed efficiently, are limited, and achieve optimal computational intractability in large, high-dimensional spaces. To achieve this, versatile, lightweight portrayals of the human inner state and modern algorithms offer great hope for reasoning.
OBJECTIVES: In this manuscript, the Interaction Modeling and Classification Scheme (IMCS) is introduced to improve the accuracy of HRI. This scheme consists of two phases, namely error classification and input mapping. In the error classification process, the input is analyzed for its events and conditional discrepancies to assign appropriate responses in the input mapping phase. The joint process is aided by a linear learning model to analyze the different conditions in the event and input detection.
RESULTS: The performance of the proposed scheme shows that it is capable of improving the interaction accuracy by reducing the ratio of errors and interaction response by leveraging the information extraction from the discrete and successive human inputs.
CONCLUSION: The fetched data are analyzed by classifying the errors at the initial stage to achieve reliable responses.
Material and Methods: Drilling processes using three brands of drills attached to a robotic arm were compared in terms of thrust force, vibration, noise level, speed deviation, and temperature. A standardised experimental setup was constructed, and measurement data were analysed statistically. Identical artificial bones were drilled 10 times with each drill.
Results: Thrust force measurements, which varied through the cortex and medulla, showed expressive differences for each drill for maximum and mean values (p<0.001). Meaningful differences were obtained for mean vibration values and noise level (p<0.001). Speed variation measurements in drilling showed conspicuous differences with confident statistics (p<0.001). Induced temperature values were measured statistically for Drill 1, Drill 2, and Drill 3 as 78.38±11.49°C, 78.11±7.79°C, and 89.77±7.79°C, respectively.
Conclusion: Thrust force and drill bit temperature were strongly correlated for each drill. Vibration values and noise level, which also had an influential relationship, were in the acceptable range for all experiments. Both thrust force and speed deviation information could be used to detect the drill bit status in the bone while drilling.
METHODS: On the basis of a series of bone milling experiments with commercial artificial bones, an artificial neural network force model is developed to estimate the milling force of different bone densities as a function of the milling feed rate and spindle speed. The model estimations are used to identify the bone density at the cutting zone by comparing the actual milling force with the estimated one.
RESULTS: The verification experiments indicate the ability of the proposed method to distinguish between one cortical and two cancellous bone densities.
CONCLUSIONS: The significance of the proposed method is that it can be used to discriminate a set of different bone density layers for a range of the milling feed rate and spindle speed.
METHODS: In this study, the frequency and causes of line of sight issues is assessed using recordings of Navigation probe locations and its synchronised video recordings.
RESULTS: The mentioned experiment conducted for a series of 15 neurosurgical operations. This issue occured in all these surgeries except one. Maximum duration of issue presisting reached up to 56% of the navigation usage time.
CONCLUSIONS: The arrangment of staff and equipment is a key factor in avoiding this issue.