Lymphatic filariasis, also known as elephantiasis, is a human disease caused by parasitic worms known as filarial worms. Most cases of the disease have no symptoms. Some people, however, develop a syndrome called elephantiasis, which is marked by severe swelling in the arms, legs, breasts, or genitals. The skin may become thicker as well, and the condition may become painful. The changes to the body may harm the affected person's social and economic situation.
The following are a few examples of the trials we performed:
Our main Objective was analyzing Integration of Modern Dermatology with Ayurveda in the treatment of Lymphatic Filariasis.
Provided with data from the Institute of Applied Dermatology regarding over 2400 patients, our main Objective was to analyse this data to find trends and patterns, to aid doctors in the treatments of this disease. The data provided us with information regarding the effectiveness of a wide range of medicines including Ayurvedic and Allopathic medicines. We were also provided with data regarding the amount of time a patient spent doing Yoga, as recommended by the treating doctor.
Using this data we applied a wide range of algorithms to find trends in the data, to get a better understanding into better and more streamlined treatments tracks based on the patient. We were able to do this by performing various analyses, to find which medicine works best, or how patients from different subgroups of a population react to particular medicines.
Over the course of this project, we used multiple algorithms, to analyze the data and come up with evidence-based results. A few of the algorithms we have used:
Analysis of variance (ANOVA) is a collection of statistical models and their associated procedures used to analyze the differences among group means.
The t-test is any statistical hypothesis test in which the test statistic follows a Student's t-distribution under the null hypothesis. A t-test is most commonly applied when the test statistic would follow a norma distribution if the value of a scaling term in the test statistic were known. When the scaling term is unknown and is replaced by an estimate based on the data, the test statistics follow a Student's t distribution. The t-test was used, to determine if two sets of data are significantly different from each other.
A chi-squared test, also written as test, is any statistical hypothesis test wherein the sampling distribution of the test statistic is a chi-squared distribution when the null hypothesis is true. In our case, the test was applied when you have two categorical variables from a single population. It is used to determine whether there is a significant association between the two variables.
Repeated measures design uses the same subjects with every branch of research, including the control. For instance, repeated measurements are collected in a longitudinal study in which change over time is assessed. Over the course of this project, we followed the tasks set by a senior statistician and executed as many as we could with the data we had. A few of the ideas did not have enough data, or in the case of a few others, the data had far too many discrepancies to work with and attain useful insights.
The general procedure we followed for most of the tasks is as follows:
