Research

ABSTRACT

One of the most threatening gynaecological cancers is ovarian cancer. This study evaluates the external factors that can help in increasing or decreasing the risk of ovarian cancer and increase or decrease in survival rates of people who have ovarian cancer. Throughout the study, 39 studies were gone through to come up with conclusions. It was understood that external factors do impact these chances.

The study focuses on various factors including - occupation, dietary choices, caffeine intake, smoking habits and pollution. However, the impact varied based of many factors which were not initially considered. Such as histological subtype - for example, while smoking increased the risk of mucinous cancer, it decreased or had no association with clear cell cancer. It also varied based of the timing of the factor evaluated. Such as, the increased the risk of serous cancer only for former smokers. Additionally, a generalised factor also could not be considered. As found, while air pollution or water pollution is said to increase the risks and mortality, our study further evaluated which particular pollutants caused this increase in the risks.

This research was conducted to further our knowledge about ovarian cancer and help people take the preventive measures required. It is important that further research should be conducted to create a better understanding as this research to left us with few unanswered questions, such as the true impact of smoking on endometroid cancer. However, there were clear trends observed such as the increased risk of smoking to mucinous cancer and the increased risk of ovarian cancer due to PM2.5.

This was done in affiliation with my school and I also presented my research there.

Internal and external factors that affect the rate of getting and survival of ovarian cancer (Currently under peer review)

2024

ChatGPT and the code it produces

2023

ABSTRACT

This research paper uses GPT-3 and determines the true capability of this new revolutionizing technology. ChatGPT is said to take jobs, and one of the most important fields are software engineers that write code. While when asked by a user, ChatGPT does produce code, our research evaluated the accuracy and quality of the code produced by ChatGPT. Given different prompts the code produced was evaluated and compared with the same prompt given to a human software developer. One of the biggest inferences observed was that the most important part of the interaction with this large language model was not the code, but it primarily depended on the prompt given. This research is primarily used to better our understanding of the capabilities of ChatGPT for 2 main reasons -