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Journal of Applied Material Science & Engineering Research(AMSE)

ISSN: 2689-1204 | DOI: 10.33140/AMSE

Impact Factor: 0.98

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Regression Analysis of Biomarkers

Research Article

Using the first-order, second-order, and third-order interpolation perturbation theory from quantum mechanics of modern physics to predict the CGM sensor devices fasting plasma glucose value in the early morning, while analyzing their associated waveform shape similarities over a 14-month period based on GH-Method: math-physical medicine (No. 561)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.01

Research Article

A Summary Report Utilizing Math-Physical Medicine Models and Statistical Regression Models to Derive Practical Prediction Equations of Selected Biomarkers for Glucoses, A1C, Diabetes, and Risk Probabilities of Having Certain Chronic Disease Complications from the Collected Data of a Type 2 Diabetes Patient based on GH-Method: Math-Physical Medicine (No. 560)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.02

Research Article

Applying Linear Regression Analysis Model to Predict HbA1C Values Using the Daily Estimated Average Glucose (eAG) Values from a 14-Month Period for a type 2 Diabetes Patient based on GH-Method: Math-Physical Medicine (No. 559)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.03

Research Article

Predicting the Fasting Plasma Glucose Level Using Two Linear Regression Equations from Body Temperature and Weight in the Early Morning as Inputs over a 14-Month Period for a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 558)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.04

Research Article

Applying Linear Regression Analysis Model to Compare the Outputs of 3 Regression Predicted CVD/Stroke Risk Probabilities Using 3 Different Inputs Which are the Calculated Sensor HbA1C value over 14-Months, Combined Medical Condition Score Months, and Calculated Finger HbA1C over an 8-Year Period from the Collected Data of a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 557)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.05

Research Article

Using Regression Analysis Model to Explore the Relationship Between the Finger-Piercing Fasting Plasma Glucose at the Wake-Up Moment and Body Weight in the Early Morning over a 6.5-Year Period for a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 556)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.06

Research Article

Using Regression Analysis Model to Explore the Relationship Between the CGM Sensor Measured Fasting Plasma Glucose from Sleeping Hours and Measured Body Temperature in the Early Morning Over a One-Year Period for a Type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 555)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.07

Research Article

Using Regression Analysis Model to Explore the Hidden Linkage between the CGM Sensor Measured Fasting Plasma Glucose from Sleeping Hours and Body Temperature in Early Morning (both are 90-Days Moving Average Values) over a One-Year Period from 11/21/2020 to 11/21/2021 for a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 553)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.08

Research Article

Using Regression Analysis Models to Explore the Possible Hidden Linkage between Finger-Pierced Fasting Plasma Glucose and Three Blood Pressure Components over an Approximate 8-Year Period for a type 2 Diabetes Patient based on GH-Method: Math-Physical Medicine (No. 552)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.09

Research Article

Applying Linear and Nonlinear Regression Analysis Models to Study the Possible Relationships between Cancers Risk and CVD/Stroke Risk over a 12-Year Period for a Type 2 Diabetes Patient Based on GH-Method: MathPhysical Medicine (No. 551)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.10

Research Article

Predicted Cancer Risk Probability using Linear and Nonlinear Regression Models with Medical Condition Inputs from Chronic Diseases and Lifestyle Details Collected Data of a Type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 550)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.11

Research Article

Exploring and validating different relationships among various biomarkers by using both linear and nonlinear, single variable and multiple variables regression analysis models and collected big data of a type 2 diabetes patient based on GH-Method: math-physical medicine (No. 549)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.12

Research Article

Applying Multiple Regression Analyses Model to Predict Fasting Plasma Glucose in Early Morning based on 3 Independent Variables, Sleep Score, Weight in the Early Morning, and Daily HbA1C over a 6.5-Year Period for a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 548)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.13

Research Article

Applying Multiple Regression Analyses to Compare the Regression Predicted and Measured Body Weight Using Food Quantity and Sleep Score as Inputs over a 6.5-Year Period for a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 547)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.14

Research Article

Applying Multiple Regression Analyses to Compare the Regression Predicted and Originally Calculated CVD/Stroke Risk Probabilities Using Medical Condition and Lifestyle Detail Scores as Inputs over a 10-year Period for a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 546)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.15

Research Article

Applying Multiple Regression Analyses and Linear Elastic Glucose Theory to Analyze and Compare the Predicted and Measured Finger-Pierced Postprandial Plasma Glucose using Carbs/Sugar Intake Amount and Post-Meal Walking Steps as Inputs over 2016-2017 Period for a Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 544)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.16

Research Article

Applying Multiple Regression Analysis and Linear Elastic Glucose Theory to Analyze and Compare the Predicted Postprandial Plasma Glucose Using Carbs/Sugar Intake Amount and Post-Meal Walking Steps as Inputs over an Approximate 2-Year COVID-19 Quarantine Period from a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 543)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.17

Research Article

Analysis of the relationship between weight and sensor average FPG using 3 methods, time-domain analysis, spatial-domain analysis, and linear regression analysis, over a 3.5-year period from a type 2 diabetes patient based on GHMethod: math-physical medicine (No. 542)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.18

Research Article

Linear Regression Analysis Results of the CGM Sensor PPG Comparison Between Predicted PPG Data Using the Candlestick Model and the LEGT Model Against the Measured Sensor PPG Data During a 2-year COVID-19 Quarantine Period for a Type 2 Diabetes Patient Based on GH-Method: MathPhysical Medicine (No. 541)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.19

Research Article

Linear Regression Analysis Results of the CGM Sensor PPG Comparison Between Predicted PPG Data Using the Linear Elastic Glucose Theory (LEGT) and Measured PPG Data During a ~2-year COVID-19 Quarantine Period for a type 2 Diabetes Patient Based on GH-Method: Math-Physical Medicine (No. 540)

  • Gerald C Hsu
DOI 10.33140/JAMSER.05.04.20