There is a growing interest in using machine learning (ML) methods for causal inference due to their (nearly) automatic and flexible ability to model key quantities such as the propensity score or the outcome model. Unfortunately, most ML methods for...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Aug 5, 2020
PURPOSE: There is limited evidence of gait training using newly developed exoskeletal lower limb robot called Hybrid Assistive Limb (HAL) on the function and ability to perform ADL in stroke patients. In clinical settings, we frequently find it chall...
BACKGROUND: Doubly robust estimation produces an unbiased estimator for the average treatment effect unless both propensity score (PS) and outcome models are incorrectly specified. Studies have shown that the doubly robust estimator is subject to mor...
Acute kidney injury (AKI) after partial nephrectomy is attributed to parenchymal reduction and ischemia, but the extent of its effect remains unclear. This study aimed to compare the incidence of postoperative AKI among surgical modalities, robot-as...
Modern survey methods may be subject to non-observable bias, from various sources. Among online surveys, for example, selection bias is prevalent, due to the sampling mechanism commonly used, whereby participants self-select from a subgroup whose cha...
BACKGROUND: Several authors claimed that the Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) needs a prolonged learning curve, and outcomes during this phase could be suboptimal.
General thoracic and cardiovascular surgery
Feb 13, 2020
OBJECTIVES: Robot-assisted thoracoscopic surgery (RATS) for primary lung cancer has been spreading rapidly in Japan. While RATS has various technical advantages over video-assisted thoracoscopic surgery (VATS), the quality of surgery from an oncologi...