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Multivariate Analysis

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Impact of robotics and a suspended lead suit on physician radiation exposure during percutaneous coronary intervention.

Cardiovascular revascularization medicine : including molecular interventions
BACKGROUND: Reports of left-sided brain malignancies among interventional cardiologists have heightened concerns regarding physician radiation exposure. This study evaluated the impact of a suspended lead suit and robotic system on physician radiatio...

Predictors of in-hospital mortality following major lower extremity amputations in type 2 diabetic patients using artificial neural networks.

BMC medical research methodology
BACKGROUND: Outcome prediction is important in the clinical decision-making process. Artificial neural networks (ANN) have been used to predict the risk of post-operative events, including survival, and are increasingly being used in complex medical ...

Inferring Weighted Directed Association Network from Multivariate Time Series with a Synthetic Method of Partial Symbolic Transfer Entropy Spectrum and Granger Causality.

PloS one
Complex network methodology is very useful for complex system explorer. However, the relationships among variables in complex system are usually not clear. Therefore, inferring association networks among variables from their observed data has been a ...

Assessing Hospital Performance After Percutaneous Coronary Intervention Using Big Data.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Although risk adjustment remains a cornerstone for comparing outcomes across hospitals, optimal strategies continue to evolve in the presence of many confounders. We compared conventional regression-based model to approaches particularly ...

Incidence of severe renal dysfunction among individuals taking warfarin and implications for non-vitamin K oral anticoagulants.

American heart journal
BACKGROUND: The purpose of this study is to assess incidence and risk factors for severe renal dysfunction in patients requiring oral anticoagulation to help guide initial drug choice and provide a rational basis for interval monitoring of renal func...

Surface Adsorbed Antibody Characterization Using ToF-SIMS with Principal Component Analysis and Artificial Neural Networks.

Langmuir : the ACS journal of surfaces and colloids
Artificial neural networks (ANNs) form a class of powerful multivariate analysis techniques, yet their routine use in the surface analysis community is limited. Principal component analysis (PCA) is more commonly employed to reduce the dimensionality...

Modeling the reflection of Photosynthetically active radiation in a monodominant floodable forest in the Pantanal of Mato Grosso State using multivariate statistics and neural networks.

Anais da Academia Brasileira de Ciencias
The study of radiation entrance and exit dynamics and energy consumption in a system is important for understanding the environmental processes that rule the biosphere-atmosphere interactions of all ecosystems. This study provides an analysis of the ...

Robot-assisted versus laparoscopic rectal resection for cancer in a single surgeon's experience: a cost analysis covering the initial 50 robotic cases with the da Vinci Si.

International journal of colorectal disease
PURPOSE: The aim of this study is to compare surgical parameters and the costs of robotic surgery with those of laparoscopic approach in rectal cancer based on a single surgeon's early robotic experience.

Using machine learning to predict radiation pneumonitis in patients with stage I non-small cell lung cancer treated with stereotactic body radiation therapy.

Physics in medicine and biology
To develop a patient-specific 'big data' clinical decision tool to predict pneumonitis in stage I non-small cell lung cancer (NSCLC) patients after stereotactic body radiation therapy (SBRT). 61 features were recorded for 201 consecutive patients wit...

A multiple hold-out framework for Sparse Partial Least Squares.

Journal of neuroscience methods
BACKGROUND: Supervised classification machine learning algorithms may have limitations when studying brain diseases with heterogeneous populations, as the labels might be unreliable. More exploratory approaches, such as Sparse Partial Least Squares (...