5 papers
Towards Fair and Efficient De-identification: Quantifying the Efficiency and Generalizability of De-identification Approaches
Noopur Zambare, Kiana Aghakasiri, Carissa Lin +3
Large language models (LLMs) have shown strong performance on clinical de-identification, the task of identifying sensitive identifiers to protect privacy. However, previous work h…
Not What the Doctor Ordered: Surveying LLM-based De-identification and Quantifying Clinical Information Loss
Kiana Aghakasiri, Noopur Zambare, JoAnn Thai +4
De-identification in the healthcare setting is an application of NLP where automated algorithms are used to remove personally identifying information of patients (and, sometimes, p…
Comparing Multiclass Classification Algorithms for Financial Distress Prediction
Noopur Zambare, Ravindranath Sawane
In this study, we explore how to improve the functionality of multiclass classification algorithms. We used a benchmark dataset from Kaggle to create a framework. They have been us…
AIOptimizer - Software performance optimisation prototype for cost minimisation
Noopur Zambare
This study presents AIOptimizer, a prototype for a cost-reduction-based software performance optimisation tool. The study focuses on the design elements of AIOptimizer, including u…
AROhI: An Interactive Tool for Estimating ROI of Data Analytics
Noopur Zambare, Jacob Idoko, Jagrit Acharya +1
The cost of adopting new technology is rarely analyzed and discussed, while it is vital for many software companies worldwide. Thus, it is crucial to consider Return On Investment…