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Roux-en-Y gastric bypass (RYGB) is a treatment for severe obesity. However, many patients have insufficient total weight loss (TWL) after RYGB. Although multiple factors have been involved, their influence is incompletely known. The aim of this exploratory study was to evaluate the feasibility and reliability of the use of machine learning (ML) techniques to estimate the success in weight loss after RYGP, based on clinical, anthropometric and biochemical data, in order to identify morbidly obese patients with poor weight responses. We retrospectively analyzed 118 patients, who underwent RYGB at the Hospital Clínico Universitario of Valencia (Spain) between 2013 and 2017. We applied a ML approach using local linear embedding (LLE) as a tool for the evaluation and classification of the main parameters in conjunction with evolutionary algorithms for the optimization and adjustment of the parameter model. The variables associated with one-year postoperative %TWL were obstructive sleep apnea, osteoarthritis, insulin treatment, preoperative weight, insulin resistance index, apolipoprotein A, uric acid, complement component 3, and vitamin B12. The model correctly classified 71.4% of subjects with TWL < 30% although 36.4% with TWL ≥ 30% were incorrectly classified as "unsuccessful procedures". The ML-model processed moderate discriminatory precision in the validation set. Thus, in severe obesity, ML-models can be useful to assist in the selection of patients before bariatric surgery.

Background: The state of the art in computer modeling of radiofrequency catheter ablation (RFCA) only considers a static situation, i.e. it ignores ablation electrode displacements induced by tissue movement due to heartbeats. This feature is theoretically required, since heartbeat-induced changes in contact force can be detected during this clinical procedure., Methods: We built a 2D RFCA model coupling electrical, thermal and mechanical problems and simulated a standard energy setting (25 W-30 s). The mechanical interaction between the ablation electrode and tissue was dynamically modeled to reproduce heartbeat-induced changes in the electrode insertion depth from 0.86 to 2.05 mm, which corresponded with contact forces between 10 and 30 g when cardiac tissue was modeled by a hyperelastic Neo-Hookean model with a Young's modulus of 75 kPa and Poisson's ratio of 0.49., Results: The lesion size computed in the dynamic case was 6.04 mm deep, 9.48 mm maximum width and 6.98 mm surface width, which is within the range of previous experimental results based on a beating heart for a similar energy setting and contact force. The lesion size was practically identical (less than 0.04 mm difference) in the static case with the electrode inserted to an average depth of 1.46 mm (equivalent to 20 g contact force)., Conclusions: The RFCA model including heartbeat-induced electrode displacement predicts lesion depth reasonably well compared to previous experimental results based on a beating heart model., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This paper presents a real-time global path planning method for mobile robots using harmonic functions, such as the Poisson equation, based on the Proper Generalized Decomposition (PGD) of these functions. The main property of the proposed technique is that the computational cost is negligible in real-time, even if the robot is disturbed or the goal is changed. The main idea of the method is the off-line generation, for a given environment, of the whole set of paths from any start and goal configurations of a mobile robot, namely the computational vademecum, derived from a harmonic potential field in order to use it on-line for decision-making purposes. Up until now, the resolution of the Laplace or Poisson equations has been based on traditional numerical techniques unfeasible for real-time calculation. This drawback has prevented the extensive use of harmonic functions in autonomous navigation, despite their powerful properties. The numerical technique that reverses this situation is the Proper Generalized Decomposition. To demonstrate and validate the properties of the PGD-vademecum in a potential-guided path planning framework, both real and simulated implementations have been developed. Simulated scenarios, such as an L-Shaped corridor and a benchmark bug trap, are used, and a real navigation of a LEGO ® MINDSTORMS robot running in static environments with variable start and goal configurations is shown. This device has been selected due to its computational and memory-restricted capabilities, and it is a good example of how its properties could help the development of social robots.

Background and Objectives: A constant voltage (DC voltage) is usually used in radiofrequency ablation (RFA) computer models to mimic the radiofrequency voltage. However, in some cases a low frequency sine wave voltage (AC voltage) may be used instead. Our objective was to assess the thermal impact of replacing DC voltage by low-frequency AC voltage in RFA computer modeling., Methods: A 2D model was used consisting of an ablation electrode placed perpendicular to the tissue fragment. The Finite Element method was used to solve a coupled electric-thermal problem. Quasi-static electrical approximation was implemented in two ways (both with equivalent electrical power): (1) by a constant voltage of 25 V in the ablation electrode (DC voltage), and (2) applying a sine waveform with peak amplitude of 25√2 V (AC voltage). The frequency of the sine signal (f AC ) varied from 0.5 Hz to 50 Hz., Results: Sine wave thermal oscillations (at twice the f AC frequency) were observed in the case of AC voltage, in addition to the temperature obtained by DC voltage. The amplitude of the oscillations: (1) increased with temperature, remaining more or less constant after 30 s; (2) was of up to ±3 °C for very low f AC values (0.5 Hz); and (3) was reduced at higher f AC values and with distance from the electrode (almost negligible for distances > 5 mm). The evolution of maximum lesion depth and width were almost identical with both DC and AC., Conclusions: Although reducing f AC reduces the computation time, thermal oscillations appear at points near the electrode, which suggests that a minimum value of f AC should be used. Replacing DC voltage by low-frequency AC voltage does not appear to have an impact on the lesion depth., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020. Published by Elsevier B.V.)