Sex and race and/or ethnicity differences in patients undergoing radiofrequency ablation for Barrett\u27s esophagus: results from the U.S. RFA Registry.

BACKGROUND: Little is known about differences in Barrett\u27s esophagus (BE) characteristics by sex and race and/or ethnicity or these differences in response to radiofrequency ablation (RFA). OBJECTIVE: We compared disease-specific characteristics, treatment efficacy, and safety outcomes by sex and race and/or ethnicity in patients treated with RFA for BE. DESIGN: The U.S. RFA patient registry is a multicenter collaboration reporting processes and outcomes of care for patients treated with RFA for BE. PATIENTS: Patients enrolled with BE. INTERVENTIONS: RFA. MAIN OUTCOME MEASUREMENTS: We assessed safety (stricture, bleeding, perforation, hospitalization), efficacy (complete eradication of intestinal metaplasia [CEIM]), complete eradication of dysplasia, and number of treatments to CEIM by sex and race and/or ethnicity. RESULTS: Among 5521 patients (4052 men; 5126 white, 137 Hispanic, 82 African American, 40 Asian, 136 heritage not identified), women were younger (60.0 vs 62.1 years) and had shorter BE segments (3.2 vs 4.4 cm) and less dysplasia (37% vs 57%) than did men. Women were almost twice as likely to stricture (odds ratio 1.7; 95% confidence interval, 1.2-2.3). Although white patients were predominantly male, about half of African Americans and Asians with BE were female. African Americans and Asians had less dysplasia than white patients. Asians and African Americans had more strictures than did white patients. There were no sex or race differences in efficacy. LIMITATIONS: Observational study with non-mandated paradigms, no central laboratory for reinterpretation of pathology. CONCLUSION: In the U.S. RFA patient registry, women had shorter BE segments and less-aggressive histology. The usual tendency toward BE in men was absent in African Americans and Asians. Posttreatment stricture was more common among women and Asians. RFA efficacy did not differ by sex or race

Towards game theoretic AV controllers: measuring pedestrian behaviour in Virtual Reality

Understanding pedestrian interaction is of great importance for autonomous vehicles (AVs). The present study investigates pedestrian behaviour during crossing scenarios with an autonomous vehicle using Virtual Reality. The self-driving car is driven by a game theoretic controller which adapts its driving style to pedestrian crossing behaviour. We found that subjects value collision avoidance about 8 times more than saving 0.02 seconds. A previous lab study found time saving to be more important than collision avoidance in a highly unrealistic board game style version of the game. The present result suggests that the VR simulation reproduces real world road-crossings better than the lab study and provides a reliable test-bed for the development of game theoretic models for AVs

Unfreezing autonomous vehicles with game theory, proxemics, and trust

Recent years have witnessed the rapid deployment of robotic systems in public places such as roads, pavements, workplaces and care homes. Robot navigation in environments with static objects is largely solved, but navigating around humans in dynamic environments remains an active research question for autonomous vehicles (AVs). To navigate in human social spaces, self-driving cars and other robots must also show social intelligence. This involves predicting and planning around pedestrians, understanding their personal space, and establishing trust with them. Most current AVs, for legal and safety reasons, consider pedestrians to be obstacles, so these AVs always stop for or replan to drive around them. But this highly safe nature may lead pedestrians to take advantage over them and slow their progress, even to a complete halt. We provide a review of our recent research on predicting and controlling human–AV interactions, which combines game theory, proxemics and trust, and unifies these fields via quantitative, probabilistic models and robot controllers, to solve this “freezing robot” problem

Evaluation Of OSMC Open Source Motor Driver for Reproducible Robotics Research

There is a growing need for open source hardware (OSH) subcomponents to be evaluated. Most robotic systems are ultimately based upon motors which are driven to move either to certain positions, as in robot arms, or to certain velocities, as in wheeled mobile robots. We evaluate a state of the art OSH driver, OSMC, for such systems, and contribute new Open Source Software to control it. Our findings suggest that OSMC is now mature enough to replace closed-source motor drivers in medium-size robots such as agri-robots and last mile delivery vehicles