Other Computer Engineering Commons^™

Evaluating Ai Language Models For Patient Queries On Total Knee Replacement (Tkr), Anesu Karen Murambadoro, Victoria Elizondo, Brianna Guillen, Matthew Hnatow, Michael Sander

Research Colloquium

Introduction: Within the past few years, large language models (LLMs) (ChatGPT, LLaMa 3, Microsoft Copilot) have increasingly become a resource that patients engage with to learn about health care procedures, including total knee replacement (TKR). Previous studies have analyzed the efficacy of large language models in providing accurate and relevant responses to questions about various procedures. Our study aims to evaluate the clarity, validity, and understandability of LLMs to patient questions about total knee replacement and assess the consistency of these models and their effectiveness in providing accurate, valid, and guideline-adherent information to patients.

Methods: We selected 30 frequently asked …

First-Year Engineering Students And Genai: Experience, Attitudes, Trust, And Ethics., Elisabeth Thomas, Cenetria Crockett, Campbell Rightmyer Bego

Undergraduate Research Events

Generative AI (GenAI) has the potential to benefit student learning by offering personalized feedback, idea generation, research, and analysis support, writing aid, and administrative support (Chan and Hu, 2023; Zhang, 2023). However, if used inappropriately, the same tools can lead to false/biased content creation and reduced ethical awareness leading to possible academic dishonesty and privacy issues (Schwartz, 2016; Wu, 2023). At this early stage, ethical standards and professorial guidance are unavailable, so it is important to understand what students are thinking about the recent technologies (Shen et al., 2013). Spring 2023 survey results revealed that some students used ChatGPT, a …

Multi-Perspective Analysis For Derivative Financial Product Prediction With Stacked Recurrent Neural Networks, Natural Language Processing And Large Language Model, Ethan Lo

Dissertations, Theses, and Capstone Projects

This study developed a multi-perspective, AI-powered model for predicting E-Mini S&P 500 Index Futures prices, tackling the challenging market dynamics of these derivative financial instruments. Leveraging FinBERT for analysis of Wall Street Journal data alongside technical indicators, trader positioning, and economic factors, my stacked recurrent neural network built with LSTMs and GRUs achieves significantly improved accuracy compared to single sub-models. Furthermore, ChatGPT generation of human-readable analysis reports demonstrates the feasibility of using large language models in financial analysis. This research pioneers the use of stacked RNNs and LLMs for multi-perspective financial analysis, offering a novel blueprint for automated prediction and …