scholarly journals Principal Component-Based Logistical Regression Algorithms to Predict Health care Accessibility for Texas Medicaid Gap

2021 ◽  
Author(s):  
Jinting Zhang ◽  
Xiu Wu
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Good Health ◽  
Poverty Line ◽  
Component Analysis ◽  
Health Condition ◽  
Quantitative Evidence ◽  
Regression Algorithms ◽  
Logistical Regression ◽  
Scientific Judgment

Abstract Background12 states without expanded Medicaid caused 2 million people who were under the poverty line across the U.S to be in Medicaid limbo and not eligible for subsidized health plans on the Affordable Care Act insurance exchanges. In order to amplify geographic equity, this paper aims to explore the health access for Medicaid gaps in Texas. MethodsPrincipal Component-based logistical regression algorithms (PCA-LA) is provided data visualization and comparison in between unadjusted and adjusted Medicaid programs. Initially, Principal Component Analysis (PCA) eliminated well-known multiplicity problems between explanatory variables in the application of epidemiology. Optimized the traditional logistical Regression (LR), the PCA-LA method, is considered health status (HS) as a dependent variable with 0 (“poor” health) and 1 (“good” health), fourteen social-economic indexes as independent variables. ResultsAfter Principal Component Analysis (PCA), four composite components incorporated health conditions (i.e., “no regular source of care” (NRC), “Last check up more than a year ago” (LCT)), demographic impacts (i.e., four categorized adults (AS)), education (ED), and marital status (MS). Compared to the unadjusted LA, direct adjusted LA, and PCA-unadjusted LA three methods, the PCA-LA approach exhibited objective and reasonable outcomes in presenting an Odd Ratio (OR). They included that health condition is positively significant to HS due to beyond 1 OR, and negatively significant to ED, AS, and MS due to less than 1 OR. ConclusionsThis paper provided quantitative evidence for the Medicaid gap in Texas to extend Medicaid, exposed healthcare geographical inequity, offered a sight for the Centers for Disease Control and Prevention (CDC) to raise researchable direction of the Medicaid program and make a timely scientific judgment of Texas healthcare accessibility.

Ridge Estimation and Principal Component Analysis to Solve an Ill-Conditioned Problem of Estimating Unmeasured Gas Turbine Parameters

2013 ◽  
Author(s):  
Maksim Shevchenko ◽  
Sergiy Yepifanov ◽  
Igor Loboda
Keyword(s):  
Principal Component Analysis ◽  
Gas Turbine ◽  
Measurement Errors ◽  
Principal Component ◽  
Component Analysis ◽  
Gas Turbine Engine ◽  
Health Condition ◽  
Component Level ◽  
Estimation Errors ◽  
Turbine Engine

This paper addresses the problem of estimation of unmeasured gas turbine engine variables using statistical analysis of measured data. Possible changes of an engine health condition and lack of information about these changes caused by limited instrumentation are taken into account. Engine thrust is under consideration as one of the most important unmeasured parameters. Two common methods of aircraft gas turbine engine (GTE) thrust monitoring and their errors due to health condition changes are analyzed. Additionally, two mathematical techniques that allow reducing in-flight thrust estimation errors in the case of GTE deterioration are suggested and verified in the paper. They are a ridge trace and a principal component analysis. A turbofan engine has been chosen as a test case. The engine has five measured variables and 23 health parameters to describe its health condition. Measurement errors are simulated using a generator of random numbers with the normal distribution. The engine is presented in calculations by its nonlinear component level model (CLM). Results of the comparison of thrust estimates computed by the CLM and the proposed techniques confirm accuracy of the techniques. The regression model on principal components has demonstrated the highest accuracy.

scholarly journals Predict Health Care Accessibility for Texas Medicaid Gap

Healthcare ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1214
Author(s):  
Jinting Zhang ◽  
Xiu Wu
Keyword(s):  
Insurance Coverage ◽  
Principal Component ◽  
Poverty Line ◽  
The United States ◽  
Health Condition ◽  
Quantitative Evidence ◽  
Regular Source ◽  
Control And Prevention ◽  
Unique Approach ◽  
Source Of Care

Medicaid is a unique approach in ensuring the below poverty population obtains free insurance coverage under federal and state provisions in the United States. Twelve states without expanded Medicaid caused two million people who were under the poverty line into health insecurity. Principal Component-based logistical regression (PCA-LA) is used to consider health status (HS) as a dependent variable and fourteen social-economic indexes as independent variables. Four composite components incorporated health conditions (i.e., “no regular source of care” (NRC), “last check-up more than a year ago” (LCT)), demographic impacts (i.e., four categorized adults (AS)), education (ED), and marital status (MS). Compared to the unadjusted LA, direct adjusted LA, and PCA-unadjusted LA three methods, the PCA-LA approach exhibited objective and reasonable outcomes in presenting an odd ratio (OR). They included that health condition is positively significant to HS due to beyond one OR, and negatively significant to ED, AS, and MS. This paper provided quantitative evidence for the Medicaid gap in Texas to extend Medicaid, exposed healthcare geographical inequity, offered a sight for the Centers for Disease Control and Prevention (CDC) to improve the Medicaid program and make political justice for the Medicaid gap.

scholarly journals Facial Landmarks Detection on Faulty Datasets with Regression Trees and Principal Component Analysis Parametrization

2018 ◽  
Author(s):  
Abner S. Nascimento ◽  
Danilo A. Oliveira ◽  
Maria Raquel L. De Couto ◽  
Iális C. De Paula Júnior
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Regression Trees ◽  
Component Analysis ◽  
Parametric Models ◽  
Essential Step ◽  
Proposed Model ◽  
Combined Use ◽  
Regression Algorithms ◽  
Missing Labels

Tracking landmarks points of the human face is an essential step for the construction of interfaces capable of taking advantage of the communicative potential of facial expressions. Many strategies based on parametric models and regression algorithms with boosting can be applied to this problem. This paper proposes a solution based on the combined use of principal component analysis and regression trees. The main purpose of the presented method is to reduce the sensibility of the system to the presence of missing labels when trained with faulty datasets, by the adoption of corrective heuristics. On such cases, the proposed model achieves performance similar to the reference results, obtained by training on fault free datasets.

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl
Keyword(s):  
Principal Component Analysis ◽  
Intermittent Claudication ◽  
Completion Time ◽  
Short Form ◽  
Principal Component ◽  
Component Analysis ◽  
German Version ◽  
Average Completion Time ◽  
Sf 36 ◽  
Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

Multifactorial analysis of clinical laboratory signs, the levels of IL-17A, IL-23, IL-33, IL-35, and specific antibodies in the serum of patients with Lyme borreliosis without erythema migrans

2020 ◽  
Vol 4 (11) ◽  
pp. 676-681
Author(s):  
V.V. Sapozhnikova ◽  
◽  
A.L. Bondarenko ◽  
Keyword(s):  
Principal Component Analysis ◽  
Lyme Borreliosis ◽  
Clinical Laboratory ◽  
Acute Infection ◽  
Erythema Migrans ◽  
Principal Component ◽  
Component Analysis ◽  
Control Group ◽  
Multifactorial Analysis ◽  
Specific Antibodies

Aim: to determine the association between clinical laboratory parameters, the production of cytokines (IL-17A, -23, -33, -35), and specific IgM and IgG in the serum of patients with Lyme borreliosis without erythema migrans. Patients and Methods: complete blood count, the concentrations of IL-17A, -23, -33, -35, and the levels of specific IgM and IgG were measured during acute infection and convalescence (n=30). The control group included age- and sex-matched healthy individuals (n=30). Statistical analysis was performed using the StatSoft Statistica v 10.0 software (parametric and non-parametric methods and multifactorial analysis, i.e., principal component analysis). Results: most (80%) patients with Lyme borreliosis without erythema migrans are the people of working age. In most patients, the combination of the specific antibodies against Borrelia afzelii and Borrelia garinii (76.7%) and severe intoxication and inflammatory process (100%) were detected. Moderate and severe disease associated with meningism was diagnosed in 90% and 10%, respectively. The mean duration of hectic period was 8.3±1.27 days. Abnormal ECG was reported in 40% of patients, i.e., conduction abnormalities in 20%, sinus bradycardia in 16.7%,and sinus tachycardia in 3.3%. The clinical laboratory signs of hepatitis without jaundice were identified in 26.7%. During treatment, the significant reduction in band and segmented neutrophil counts as well as the significant increase in platelet count were revealed compared to these parameters at admission. Abnormal cytokine levels (i.e., the increase in IL-17A, -23, -33 and the deficiency of IL-35) were detected. Conclusions: multifactorial analysis has demonstrated that the severity of immunological abnormalities in patients with Lyme borreliosis without erythema migrans is associated with fever, cardiac and liver disorders, the high levels of IL-23 and IL-33, and the lack of IL-35 and specific IgM and IgG. KEYWORDS: tick-borne borreliosis, Lyme disease without erythema migrans, clinical laboratory signs, cytokines, specific antibodies, multifactorial analysis, principal component analysis. FOR CITATION: Sapozhnikova V.V., Bondarenko A.L. Multifactorial analysis of clinical laboratory signs, the levels of IL-17A, IL-23, IL-33, IL-35, and specific antibodies in the serum of patients with Lyme borreliosis without erythema migrans. Russian Medical Inquiry. 2020;4(11):676–681. DOI: 10.32364/2587-6821-2020-4-11-676-681.

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