Reimagining Multidisciplinary Teams: Challenges and Opportunities for LLMs in Cancer MDTs
Soraia Figueiredo Paulo, Isabel Neto, Nuno Leitão Figueiredo, Daniel Simões Lopes, Hugo Nicolau
摘要
Multidisciplinary teams are crucial in tailoring cancer care through collaborative decision-making involving several clinical specialties. The inherent complexity of clinical cases, the increasing abundance of unstructured textual data, and the time restrictions of professionals pose significant challenges to team coordination and patient care. This creates an opportunity for generative AI technologies, such as LLMs, to enhance collaborative work. Despite the growing interest in HCI research to explore LLMs in healthcare, we have yet to understand clinicians' perspectives on this emerging technology in multidisciplinary teams. Our work investigates the challenges, expectations and opportunities for LLMs in this context through a speculative approach. We leveraged the Futures Cone framework and conducted a qualitative study with 11 physicians from different cancer multidisciplinary teams. We contribute with an analysis of themes that emerged from individual interviews and a focus group, highlighting LLMs' potential to enhance and reshape multidisciplinary teams' practices. In addition, we uncover concerns and coping strategies related to LLMs' adoption and provide a set of design opportunities to inform the development of technologies for LLM-enhanced multidisciplinary teams.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它它引用的顶会 Paper10
- Language Models are Few-Shot LearnersTom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah 等NeurIPS 2020 · 被引用 64,255 次
- Explanations Can Reduce Overreliance on AI Systems During Decision-MakingHelena Vasconcelos, Matthew Jörke, Madeleine Grunde-McLaughlin, Tobias Gerstenberg 等CSCW 2023 · 被引用 362 次
- Expanding Modes of Reflection in Design FuturingSandjar Kozubaev, Chris Elsden, Noura Howell, Marie Louise Juul Søndergaard 等CHI 2020 · 被引用 171 次
- Investigating AI Teammate Communication Strategies and Their Impact in Human-AI Teams for Effective TeamworkRui Zhang, Wen Duan, Christopher Flathmann, Nathan J. McNeese 等CSCW 2023 · 被引用 98 次
- Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision MakingMin Hun Lee, Chong Jun ChewCSCW 2023 · 被引用 74 次
相关 Paper
- Exploring the Future of AI in Clinical Collaboration: A Study on Tumor Board Case PreparationJiachen Li, Amanda K. Hall, Ruican Rachel Zhong, Selin S. Everett 等CHI 2026 · 被引用 1 次
- Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision-Language Applications for RadiologyNur Yildirim, Hannah Richardson, Maria Teodora Wetscherek, Junaid Bajwa 等CHI 2024 · 被引用 81 次
- Current and Future Use of Large Language Models for Knowledge WorkMichelle Brachman, Amina H. El-Ashry, Casey Dugan, Werner GeyerCSCW 2025 · 被引用 10 次
- CliCARE: Grounding Large Language Models in Clinical Guidelines for Decision Support over Longitudinal Cancer Electronic Health RecordsDongchen Li, Jitao Liang, Wei Li, Xiaoyu Wang 等AAAI 2026 · 被引用 1 次
- Human-Algorithmic Interaction Using a Large Language Model-Augmented Artificial Intelligence Clinical Decision Support SystemNiroop Channa Rajashekar, Yeo Eun Shin, Yuan Pu, Sunny Chung 等CHI 2024 · 被引用 85 次
