Individual Project 1
Introduction
This report will cover the dataset diabetes details from Efron et al.(2003). Throughout this report, we will explore the potential relationship between the ten predictor variables: age, sex, BMI, average blood pressure, and six blood serum measurements (tc, ldl, hdl, tch, ltg, glu) on a quantitative measure of disease progression one year after the baseline. There are 442 diabetes patients, or records in the dataset. In this report, we will explore different methods and cross validation techniques to understand these sample datasets leveraging linear regression, ridge regression, lasso method and metrics like our MSE, the mean prediction error and standard errors of the test dataset. First, we will
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With the positive coefficients, we will see an increase in one unit of each variable separately compared with the advancement in diabetes. With a 0.05 parameter, the linear regression model selects 5 predictor variables with significance, age, tc, ldl, tch, and glu. To validate the assumption, we can plot the residuals versus the fitted values to see if there are any indications of signs of random distributions. For the residual plot, we see there are no indications or violations of random distribution and can calculate the MSE of the model, which is 3111.265. Next, we will leverage the best subset method to select the predictor variables that are truly impactful to the model.
Best Subset Model
With our best subset method, we can leverage our lowest BIC metric to select the best model. We can plot out best subset method and pinpoint the number of variables to select. The plot below showcases that the lowest point or value of BIC, contains 6 variables. We leverage the BIC metric because it places a penalty on models with more or many variables. Meaning, the mode variable a model has, the bigger the penalty. We can review the coefficients, standard errors, t-value, and the p-values for the best subset method with the significant six variables. Our MSE metric for the 6-variable best subset model is 3090.483, a slight decrease from our linear regression model.
Best Subset Model with 10-fold Cross
The charity that we researched was The Alberta Diabetes Foundation. We chose this agency because it affects both of us. I know four people who have had or have diabetes. My dad had type two diabetes, my partner's mom has type 1, so does my sister’s friend and my friend. My dad has managed to lose enough weight through exercise and dieting to get rid of his diabetes. My dad has lost over one hundred lbs and hasn’t had pop in over two and a half years. My sister’s friend has had type 1 diabetes for a long time and has many struggles with her diabetes like fainting. My friend has managed to still do the things she loves with her diabetes. Riley’s mom has type 1 diabetes and I know it has affected them a lot. Our charity helps many
National vital statistics data are collected from birth, death and marriage certificates. Mandatory data collection requirements in the United States provide the most consistent and generally highest quality data available for determining the health status of our population (Williams, 2008). There was an expansion in diabetes related mortality over the previous decade, the expanded mortality shows up for the most part ascribed to the pervasiveness of cardiovascular sicknesses. In this manner, arrangement policy makers should pay more considerations to diabetes essential counteractive action to lessen the rate while additionally setting a need on the burden of cardiovascular sicknesses to decrease the weight of
These measurements include the assessment of risk factors[61], quality of care[62], diagnostic criteria[63], etc. Most of these studies used rule-based method[62, 63] to detect clearly defined and less complex (fewer expression variations) measurements, such as glucose level and body mass index. For some ambiguous and complex measurements, such as coronary artery disease and obesity status, machine learning plus external terminologies[61] are often
Diabetes is everywhere in the world now, since more people have it than ever before. Still, we have a lot more to learn about this illness if we are to fight and overcome it. There are some things about diabetes that most people just don't know. Stay tuned for part two, coming soon!
American Diabetes Association was founded to stop the rising percentage of diabetes patients and to face the negatives effects of it. The ADA is very important because diabetes is a serious and dangerous condition. It is concerning how many adults and young people had been affected by diabetes. The country needs an association like this to conduct and administrate the funding to prevent and develop researches for the
American Diabetes Association has a long history of research support and engagement. The first direct ADA research were awarded in 1952, and in the late 1970s, the ADA research funding was centralized into a program model after that of the National Institute of Health (NIH), with operational and scientific oversight housed in the national office. Founded in October 1994, the ADA Foundation was created to substantially accelerate the Association 's ability to raise major gifts to directly fund diabetes research. Now the ADA is a volunteer-driven organization, with about 90 local offices above the United States. The goal of the ADA is to prevent and cure diabetes and to improve the lives of all people affected by diabetes. The burdens of diabetes are enormous and escalating at an alarming rate. About 26 million Americans have the disease, and over 10% of the total adult population and over 25% of the population aged 65 years and older. If present trends continue, as many as one in three Americans adult will be diagnosed with diabetes by 2050; in majority of cases will include older adults and racial ethnic minorities.
The study had an overall total of 1150 participants. Although there were many participants to begin with, they did not provide all of the feedback the researchers had requested. This resulted in the expulsion of their participation, so their results were not included in the final reports of the study. The number of patients that did provide the essential information added up to a total of 901. The profile for a participant was a patients diagnosed with Type 2 diabetes in the last 6 months, but has been diagnosed no more than 10 years ago. They had to be between 35-70 years of age. Their BMI had to be more or less than 24 kg/m2 and have an HbA1c more or less than 6.5%. They also had to have treatment with a diet or oral glucose lowering medication. Those needing insulin shots, had been diagnosed with chronic diseases, or had a change in diet or lifestyle 3 months prior to the study were not included in the overall
Diabetes Data for Bexar County: According to the 2014 City of San Antonio Diabetes Fact Sheet, The percentage of adults with diabetes in Bexar county has been on the increase in the last few years. In 2012, 11.4% of the population in Bexar county had been diagnosed with diabetes; in 2013, number of diagnosed residents increased to 12.7%, and in 2014, it had increased to14.2%. Diabetes prevalence did not differ significantly between adult males (13%) and females (15%). Percentage of adults with diabetes by age was 1% for adults 18-29 years; 6% for adults age 30-44 years; 22% for people age 45-64 years and 33% for people age 65 years and older. In 2014, percentage of adults with diabetes by ethnicity was: Hispanics 15%; non-Hispanic
According to the United States Library of Medicine, diabetes is a disease that occurs when the body does not make or use insulin correctly, therefore causing fluctuating amounts of glucose in the blood. Diabetes is a disease that affects millions of adults and children from various cultures. According to the American Diabetes Association (2014), someone is diagnosed with diabetes every 19 seconds. The Center of Disease Control and Prevention most recent statistical report indicated there were 29.1 million adults and children affected by diabetes. Those numbers are astounding. Unfortunately, the American Diabetes Association (2014) estimates by year of 2050, one out of three adults will have diabetes. Therefore, it is imperative that adults take aggressive measures to prevent this disease. By the same token, diabetes diagnosed in children and adolescent is becoming more prevalent every day. The American Diabetes Association (2014) reported there were about 216, 00 children in the United States with diabetes. It is predicted that one out three children will be diagnosed with diabetes in their life. The statistics for both adults and children with diabetes are frightening; however, early detection can help lower the risk of developing the debilitating effects of diabetes.
According to the American Diabetes Association, more Americans die each year from diabetes than from AIDS and breast cancer combined. As a result, researchers have extensively studied the causes, treatments, and interventions for diabetes. Despite efforts to ameliorate its effects, diabetes remains a prevalent danger in society. In 2014, 7% of U.S. adults were living with diagnosed diabetes (Centers for Disease Control and Prevention [CDC], 2016). In Louisiana that number was even higher - 10.4% of adults have been diagnosed with diabetes. Breaking it down by age group, however, in Louisiana 3% of people aged 18 and 44 have been diagnosed, and 15.2% of people 45-64. (Centers for Disease Control and Prevention [CDC], 2015a). Several studies have predicted future rates of diabetes both in the United States and worldwide - nearly all of these studies reached a similar conclusion: rates of diabetes will continue to rise (Boyle et al., 2001).
This study utilized the Worchester Heart Attack Study data and R Studio software to predict the mortality factors for heart attack patients. The medical data include physiological measurements about heart attack patients, which serve as the independent variables, such as the heart rate, blood pressure, atria fibrillation, body mass index, cardiovascular history, and other medical signs. This study employed the techniques of supervised learning and unsupervised learning algorithms, using classification decision trees and k-means clustering, respectively. In addition to performing initial descriptive statistics to estimate the general range of critical factors correlated with heart attack patients, R Studio was used to determine the weight of each of the significant factors on the prediction in order to quantify its influence on the death of heart attack patients. Furthermore, the software was used to evaluate the accuracy of the predicted model to estimate death of heart attack patients by using a confusion matrix to compare predictions with actual data. Finally, this study reflected on the effectiveness of the data mining software conclusions, compared supervised learning and unsupervised learning, and conjectured improvements for future data mining investigations.
According to a study provided in USNews, there are regional issues when it comes to the rates of type-2 diabetes within the United States today (Seppa, 2011). The "diabetes belt" that can clearly be seen in the Southeast part of the country is one of these regional issues. Southern people, on average, tend to have a higher incidence of diabetes than people in other areas of the country. With that in mind, it is important to realize that there are various reasons why that is the case. It is not just one factor causing the problems, and it is not just the Southeast where diabetes is seen. There are other areas of the country where pockets of diabetes are seen, so no specific place or region of the country is immune to problems with diabetes. The following map shows the basic breakdown of diabetes across the country for the latest year where statistics on the issue are available (Seppa, 2011).
1. Annotated Bibliography Entry: Diabetes Education: Art, Science and Evidence (1). (2012). Hoboken, GB: Wiley-Blackwell.
Type-2 Diabetes mellitus (T2DM) is a common disease worldwide. According to the American Diabetes association (ADA), 1808 million people in the United States have been diagnosed with diabetes, and another 7 million are thought to have the disease but have not been diagnosed. (Hilaire, Woods, 2013). This disease has impacted everyone in some way. It is a controllable disease; however many individuals choose not to control it or are uneducated on how to control it. Many people with type 2 diabetes (T2DM) also have hypertension, high cholesterol, obesity, lack of physical activity, poorly controlled blood sugars, and smoking. “Current evidence supports the concept that hyperglycemia significantly contributes to the development of both cardiovascular and microvascular complications of T2DM” (Chittari, McTernan, 2011). Cardiovascular disease (CVD) remains the leading cause of death in patients with diabetes mellitus, accounting for 50% of all deaths (Campbell & Hillman, 2010).
Researcher James Levin’s “Poverty and Obesity in the U.S” from American Diabetes Association, research about the Obesity and Diabetes in Poverty counties/reigns of the United States. Levin believes poverty and obesity are linked to each other. According to Levin’s research “ People in America who live in the most poverty-dense counties are those most prone to obesity. ” . There are many reason that link poverty to obesity, but Levin believes lack of fresh food and inactivity has a huge role in chronic metabolic disease (obesity and diabetes), and cardiovascular death. People who