About
My name is Nidhi, and I am currently in my 4th semester (2024) at the School of Computer Engineering (SoCE) at KLE Technological University. This portfolio is created as part of my Exploratory Data Analysis (EDA) course project to showcase the knowledge and skills acquired over the term. It serves as a comprehensive reflection on our learning journey, highlighting key insights and experiences.
The portfolio is organized into a series of tabs, each dedicated to a specific learning target, unit, or major area. These include detailed analyses, visualizations, and interpretations of data, demonstrating our ability to apply EDA techniques to real-world datasets.
The course project aims to predict the time it takes for breast cancer patients to be diagnosed with metastatic cancer, focusing on uncovering disparities in healthcare access influenced by demographics, socioeconomic factors, and climate data. Utilizing a comprehensive dataset provided by Gilead Sciences, which includes detailed patient demographics, diagnosis and treatment records, insurance coverage, geo-demographic information, and climate data at the zip code level, this project seeks to identify key factors contributing to delays in diagnosis.
Given the aggressive nature of metastatic Triple-Negative Breast Cancer (TNBC), timely diagnosis and treatment are crucial. By pinpointing the causes of diagnostic delays, the project intends to highlight and address potential healthcare disparities, ultimately aiming to improve outcomes for affected patients.