4 citations · 9 across the 10 of their papers we have counts for
10 papers
Human-LLM Dialogue Improves Diagnostic Accuracy in Emergency Care
Burcu Sayin, Ngoc Vo Hong, Ipek Baris Schlicht +8
Clinical decision-making in emergency medicine demands rapid, accurate diagnoses under uncertainty. Despite benchmark progress, evidence for LLMs as interactive aids in live physic…
Hybrid Decision Making via Conformal VLM-generated Guidance
Debodeep Banerjee, Burcu Sayin, Stefano Teso +1
Building on recent advances in AI, hybrid decision making (HDM) holds the promise of improving human decision quality and reducing cognitive load. We work in the context of learnin…
Towards Reliable Retrieval in RAG Systems for Large Legal Datasets
Markus Reuter, Tobias Lingenberg, Rūta Liepiņa +5
Retrieval-Augmented Generation (RAG) is a promising approach to mitigate hallucinations in Large Language Models (LLMs) for legal applications, but its reliability is critically de…
Zoom In Disparities in Healthcare LLM Q&A
Ipek Baris Schlicht, Burcu Sayin, Zhixue Zhao +5
Equitable access to reliable health information is vital when integrating AI into healthcare. Yet, information quality varies across languages, raising concerns about the reliabili…
MedSyn: Enhancing Diagnostics with Human-AI Collaboration
Burcu Sayin, Ipek Baris Schlicht, Ngoc Vo Hong +4
Clinical decision-making is inherently complex, often influenced by cognitive biases, incomplete information, and case ambiguity. Large Language Models (LLMs) have shown promise as…
MedGellan: LLM-Generated Medical Guidance to Support Physicians
Debodeep Banerjee, Burcu Sayin, Stefano Teso +1
Medical decision-making is a critical task, where errors can result in serious, potentially life-threatening consequences. While full automation remains challenging, hybrid framewo…
Do LLMs Provide Consistent Answers to Health-Related Questions across Languages?
Ipek Baris Schlicht, Zhixue Zhao, Burcu Sayin +2
Equitable access to reliable health information is vital for public health, but the quality of online health resources varies by language, raising concerns about inconsistencies in…
Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain
Burcu Sayin, Pasquale Minervini, Jacopo Staiano +1
We explore the potential of Large Language Models (LLMs) to assist and potentially correct physicians in medical decision-making tasks. We evaluate several LLMs, including Meditron…
Learning To Guide Human Decision Makers With Vision-Language Models
Debodeep Banerjee, Stefano Teso, Burcu Sayin +1
There is growing interest in AI systems that support human decision-making in high-stakes domains (e.g., medical diagnosis) to improve decision quality and reduce cognitive load. M…
Rethinking and Recomputing the Value of Machine Learning Models
Burcu Sayin, Jie Yang, Xinyue Chen +2
In this paper, we argue that the prevailing approach to training and evaluating machine learning models often fails to consider their real-world application within organizational o…