Search Results for author: Muhammad Aurangzeb Ahmad

Found 7 papers, 0 papers with code

Creating Trustworthy LLMs: Dealing with Hallucinations in Healthcare AI

no code implementations26 Sep 2023 Muhammad Aurangzeb Ahmad, Ilker Yaramis, Taposh Dutta Roy

Large language models have proliferated across multiple domains in as short period of time.

Validation of a Hospital Digital Twin with Machine Learning

no code implementations7 Mar 2023 Muhammad Aurangzeb Ahmad, Vijay Chickarmane, Farinaz Sabz Ali Pour, Nima Shariari, Taposh Dutta Roy

Recently there has been a surge of interest in developing Digital Twins of process flows in healthcare to better understand bottlenecks and areas of improvement.

Machine Learning Approaches for Type 2 Diabetes Prediction and Care Management

no code implementations15 Apr 2021 Aloysius Lim, Ashish Singh, Jody Chiam, Carly Eckert, Vikas Kumar, Muhammad Aurangzeb Ahmad, Ankur Teredesai

Prediction of diabetes and its various complications has been studied in a number of settings, but a comprehensive overview of problem setting for diabetes prediction and care management has not been addressed in the literature.

BIG-bench Machine Learning Diabetes Prediction +2

Emergency Department Optimization and Load Prediction in Hospitals

no code implementations6 Feb 2021 Karthik K. Padthe, Vikas Kumar, Carly M. Eckert, Nicholas M. Mark, Anam Zahid, Muhammad Aurangzeb Ahmad, Ankur Teredesai

Over the past several years, across the globe, there has been an increase in people seeking care in emergency departments (EDs).

Survey of explainable machine learning with visual and granular methods beyond quasi-explanations

no code implementations21 Sep 2020 Boris Kovalerchuk, Muhammad Aurangzeb Ahmad, Ankur Teredesai

Next, we present methods of visual discovery of ML models, with the focus on interpretable models, based on the recently introduced concept of General Line Coordinates (GLC).

BIG-bench Machine Learning LEMMA +1

The Challenge of Imputation in Explainable Artificial Intelligence Models

no code implementations29 Jul 2019 Muhammad Aurangzeb Ahmad, Carly Eckert, Ankur Teredesai

In this paper, we explore different settings where AI models with imputation can be problematic and describe ways to address such scenarios.

Explainable Models Imputation

Cannot find the paper you are looking for? You can Submit a new open access paper.