Shifat A Nowrin

Motivated graduate assistant with experience in academic and administrative support. Adaptable and quick to grasp new concepts, with a dedication to efficient information retention. Demonstrates a history of excellence in various endeavors and a commitment to fostering growth and development in both individual and team settings

https://www.researchgate.net/profile/Shifat-Nowrin

Database project: Dental Clinic Management:

A new dental clinic just opened with 10 dentists who specialized in different fields of dentistry along with the dental assistants. The new setup would be managed by an administration team consisting of five members. The clinic is expecting at least 10 patients in each field of dentistry and 100% profit at the end of the year. Hence, the dental clinic acquires a database system that could be utilized to meet the data and commercial requirements of this study.

Information and visualization project - Bone Tumor Survey

In this project, an in-depth analysis of a dataset comprising records of 500 patients diagnosed with Bone Tumors was presented. The data was collected from patients at the Memorial Sloan Kettering Cancer Center (MSKCC). This dataset includes various information for the patients.

Data Mining project - Prediction of Kidney Disease Severity Using Data Mining Techniques

This project aimed to evaluate the causes of kidney disease and its association with the severity of the kidney disease in those who have undergone hemodialysis in Data mining approach.

Machine Learning Project - Autism Prediction in Adults

This project aimed to predict the best model for an adult person having autism using this Q10 survey along with exploring the disease across gender, age, and other demographic variables.

Natural Language Processing Project- News Article Classification

We aimed to classify the news articles using different models and compared which model give the best accuracy to classify the articles.

Capstone Project - Self-Reported Oral Health Status: The NHANES study

This project aimed to examine self-reported oral health status among U.S. adults using data from three recent NHANES cycles (2015–2016, 2017–March 2020, and 2021–2023). The analysis explored the association between demographic variables—age, gender, race, educational level, and family income—and SROH outcomes, leveraging multivariable logistic regression to identify significant predictors. Results indicate that sociodemographic disparities substantially influence oral health perceptions, with education and income emerging as key determinants.