Neural networks : the official journal of the International Neural Network Society
Feb 8, 2015
In this paper, the interpolation of multivariate data by operators of the neural network type is proved. These operators can also be used to approximate continuous functions defined on a box-domain of R(d). In order to show this fact, a uniform appro...
American journal of obstetrics and gynecology
Jan 28, 2015
OBJECTIVE: Robotic gynecological surgery is feasible in obese patients, but there remain concerns about the safety of this approach because the positioning required for pelvic surgery can exacerbate obesity-related changes in respiratory physiology. ...
Prognostics is a core process of prognostics and health management (PHM) discipline, that estimates the remaining useful life (RUL) of a degrading machinery to optimize its service delivery potential. However, machinery operates in a dynamic environm...
Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional s...
INTRODUCTION: An increasing number of obese patients (body mass index [BMI] >30 kg/m(2)]) with localized prostate cancer are presenting as candidates for robot-assisted radical prostatectomy (RARP), which can be carried out using the transperitoneal ...
Journal of the American College of Surgeons
Oct 15, 2014
BACKGROUND: The indications for minimally invasive (MIS) pancreatectomy have slowly increased as experience, techniques, and technology have improved and evolved to manage malignant lesions in selected patients without compromising safety and oncolog...
Recent reports of multivariate machine learning (ML) techniques have highlighted their potential use to detect prognostic and diagnostic markers of pain. However, applications to date have focussed on acute experimental nociceptive stimuli rather tha...
European child & adolescent psychiatry
Aug 11, 2014
Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challenging. To assess the diagnostic predictive value of multiple types of data at the emergence of early-onset first-episode psychosis (FEP), various suppo...
OBJECTIVES: To develop a machine learning model to accurately predict stroke risk based on demographic and clinical data. It also sought to identify the most significant stroke risk factors and determine the optimal machine learning algorithm for str...
In the study of age estimation in living individuals, a lot of data needs to be analyzed by mathematical statistics, and reasonable medical statistical methods play an important role in data design and analysis. The selection of accurate and appropri...