AIMC Topic: Multivariate Analysis

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Obesity and perioperative pulmonary complications in robotic gynecologic surgery.

American journal of obstetrics and gynecology
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. ...

A New Multivariate Approach for Prognostics Based on Extreme Learning Machine and Fuzzy Clustering.

IEEE transactions on cybernetics
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...

Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

NeuroImage
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...

Outcomes of Extraperitoneal Robot-Assisted Radical Prostatectomy in the Morbidly Obese: A Propensity Score-Matched Study.

Journal of endourology
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 ...

Distal pancreatectomy: a single institution's experience in open, laparoscopic, and robotic approaches.

Journal of the American College of Surgeons
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...

Multivariate decoding of cerebral blood flow measures in a clinical model of on-going postsurgical pain.

Human brain mapping
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...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

European child & adolescent psychiatry
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...

Dual-stream interactive networks with pearson-mask awareness for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society
Multivariate time series forecasting (MTSF) aims to predict time series data containing multiple variates, which requires the consideration of both intra-series temporal trends and inter-series interactions. Benefiting from the success of Transformer...

Univariate versus multivariate approaches for resolving the overlapped spectra of azelastine hydrochloride and mometasone furoate.

Analytical biochemistry
Azelastine hydrochloride (AZE) and Mometasone furoate (MOM) combination is used to treat allergic rhinitis' symptoms. The aim of this work is to qualitatively and quantitatively analyze both medications using univariate and multivariate spectrophotom...

Leveraging infrared spectroscopy for cocoa content prediction: A dual approach with Kohonen neural network and multivariate modeling.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
People of all ages enjoy chocolate, and its popularity is attributed to its pleasant taste and aroma, as well as its associated health benefits. Produced through both artisanal and industrial processes, which involve harvesting, selecting, fermenting...