Symposium

Of Rising ScholarsFall 2022

Krishnaveni will be presenting at The Symposium of Rising Scholars on Saturday, September 24th! To attend the event and see Krishnaveni's presentation,

Register here!
Go to Polygence Scholars page
Krishnaveni Parvataneni's cover illustration
Polygence Scholar2022
Krishnaveni Parvataneni's profile

Krishnaveni Parvataneni

BASIS Independent Silicon ValleyClass of 2024Santa Clara, California

About

Projects

  • "How could AI assist in the prediction and search for risk factors of anorexia nervosa?" with mentor Shaan (Working project)

Project Portfolio

How could AI assist in the prediction and search for risk factors of anorexia nervosa?

Started Feb. 1, 2022

Abstract or project description

Krishnaveni's project will focus on using machine learning to predict eating disorder status using the AddHealth Dataset. The variable of interest for prediction will be the H3GH8 question - “Have you ever been told by a doctor that you have an eating disorder, such as anorexia nervosa or bulimia?”. The training features will include all other survey questions responded to by subjects that answered the above question. The project will use principal component analysis and recursive feature elimination as feature reduction methods, and will use Support Vector Machine and XGBoost models as the models of choice. The hypothesis is that features such as adoption status, gender, and abuse will be the strongest predictors of eating disorder status and that the model will have high predictive value for eating disorder status.