AIMC Topic: Factor Analysis, Statistical
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Application of Deep Neural Network Factor Analysis Model in Operating Room Management Nursing Analysis of Postoperative Infection Nursing after Thoracic Surgery.
Computational and mathematical methods in medicine
Oct 26, 2021
Thoracic surgery is the main surgical method for the treatment of respiratory diseases and lung diseases, but infections caused by improper care are prone to occur during the operation, which can induce pulmonary edema and lung injury and affect the ...
A machine learning approach for the factorization of psychometric data with application to the Delis Kaplan Executive Function System.
Scientific reports
Aug 19, 2021
While a replicability crisis has shaken psychological sciences, the replicability of multivariate approaches for psychometric data factorization has received little attention. In particular, Exploratory Factor Analysis (EFA) is frequently promoted as...
Machine Learning Reduced Gene/Non-Coding RNA Features That Classify Schizophrenia Patients Accurately and Highlight Insightful Gene Clusters.
International journal of molecular sciences
Mar 25, 2021
RNA-seq has been a powerful method to detect the differentially expressed genes/long non-coding RNAs (lncRNAs) in schizophrenia (SCZ) patients; however, due to overfitting problems differentially expressed targets (DETs) cannot be used properly as bi...
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis.
Psychometrika
Feb 2, 2021
Marginal maximum likelihood (MML) estimation is the preferred approach to fitting item response theory models in psychometrics due to the MML estimator's consistency, normality, and efficiency as the sample size tends to infinity. However, state-of-t...
Application of machine learning to the prediction of postoperative sepsis after appendectomy.
Surgery
Sep 18, 2020
BACKGROUND: We applied various machine learning algorithms to a large national dataset to model the risk of postoperative sepsis after appendectomy to evaluate utility of such methods and identify factors associated with postoperative sepsis in these...
Exploring gene-gene interaction in family-based data with an unsupervised machine learning method: EPISFA.
Genetic epidemiology
Sep 1, 2020
Gene-gene interaction (G × G) is thought to fill the gap between the estimated heritability of complex diseases and the limited genetic proportion explained by identified single-nucleotide polymorphisms. The current tools for exploring G × G were oft...
A facet atlas: Visualizing networks that describe the blends, cores, and peripheries of personality structure.
PloS one
Jul 30, 2020
We created a facet atlas that maps the interrelations between facet scales from 13 hierarchical personality inventories to provide a practically useful, transtheoretical description of lower-level personality traits. We generated this atlas by estima...
Future possibilities for artificial intelligence in the practical management of hypertension.
Hypertension research : official journal of the Japanese Society of Hypertension
Jul 13, 2020
The use of artificial intelligence in numerous prediction and classification tasks, including clinical research and healthcare management, is becoming increasingly more common. This review describes the current status and a future possibility for art...
Identifying the Symptom Severity in Obsessive-Compulsive Disorder for Classification and Prediction: An Artificial Neural Network Approach.
Behavioural neurology
Jun 22, 2020
The present study is aimed at identifying the most prominent determinants of OCD along with their strength to classify the OCD patients from healthy controls. The data for this cross-sectional study were collected from 200 diagnosed OCD patients and ...
Automated detection and classification of diabetes disease based on Bangladesh demographic and health survey data, 2011 using machine learning approach.
Diabetes & metabolic syndrome
Mar 10, 2020
BACKGROUND AND AIMS: Diabetes has been recognized as a continuing health challenge for the twenty-first century, both in developed and developing countries including Bangladesh. The main objective of this study is to use machine learning (ML) based c...
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