Laparoscopic partial nephrectomy (LPN) and robot-assisted partial nephrectomy (RAPN) are commonly used techniques for treating small renal masses. Regarding renal function (RF) preservation, no superiority of one technique over the other has yet bee...
We sought to compare the outcomes of patients who underwent an open robotic ureteroneocystostomy for ureteral obstruction. Retrospective review was performed on adult patients who underwent primary ureteroneocystostomy for obstruction from January...
BACKGROUND: Measurement of volumetric features is challenging in glioblastoma. We investigate whether volumetric features derived from preoperative MRI using a convolutional neural network-assisted segmentation is correlated with survival.
BACKGROUND: Pelvic exenteration remains a viable and effective treatment option for the management of locally advanced or recurrent pelvic malignancy. The aim of this study was to present an early experience of robotic multivisceral resection of pelv...
BACKGROUND: This study aimed to establish and validate a machine learning-based model for the prediction of early phase postoperative hypertension (EPOH) requiring the administration of intravenous vasodilators after carotid endarterectomy (CEA).
OBJECTIVES: We aimed to build a machine learning predictive model to predict the risk of prolonged mechanical ventilation (PMV) for patients with Traumatic Brain Injury (TBI).
International journal of urology : official journal of the Japanese Urological Association
Jul 7, 2020
OBJECTIVES: To compare the perioperative and oncological outcomes between robot-assisted radical cystectomy with intracorporeal urinary diversion versus open cystectomy for bladder cancer in a contemporary Enhanced Recovery After Surgery cohort.
BACKGROUND: The aims of this study were to determine the predictive value of decision support analysis for the shock wave lithotripsy (SWL) success rate and to analyze the data obtained from patients who underwent SWL to assess the factors influencin...
Psychotherapy research : journal of the Society for Psychotherapy Research
Jun 30, 2020
Decision-tree methods are machine-learning methods which provide results that are relatively easy to interpret and apply by human decision makers. The resulting decision trees show how baseline patient characteristics can be combined to predict trea...
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