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Related papers: Conversational Medical AI: Ready for Practice

200 papers

At the heart of medicine lies the physician-patient dialogue, where skillful history-taking paves the way for accurate diagnosis, effective management, and enduring trust. Artificial Intelligence (AI) systems capable of diagnostic dialogue…

Background: Globally we face a projected shortage of 11 million healthcare practitioners by 2030, and administrative burden consumes 50% of clinical time. Artificial intelligence (AI) has the potential to help alleviate these problems.…

Human-Computer Interaction · Computer Science 2025-08-01 Hashim Hayat , Maksim Kudrautsau , Evgeniy Makarov , Vlad Melnichenko , Tim Tsykunou , Piotr Varaksin , Matt Pavelle , Adam Z. Oskowitz

Healthcare conversational AI agents shouldn't be optimized only for clean benchmark accuracy in production-first regime; they must be optimized for the lived reality of patient conversations, where audio is imperfect, intent is indirect,…

The integration of voice-based AI agents in healthcare presents a transformative opportunity to bridge economic and accessibility gaps in digital health delivery. This paper explores the role of large language model (LLM)-powered voice…

Artificial Intelligence · Computer Science 2025-07-28 Bo Wen , Chen Wang , Qiwei Han , Raquel Norel , Julia Liu , Thaddeus Stappenbeck , Jeffrey L. Rogers

Large language models (LLMs) have shown considerable potential in supporting medical diagnosis. However, their effective integration into clinical workflows is hindered by physicians' difficulties in perceiving and trusting LLM…

Human-Computer Interaction · Computer Science 2026-01-28 Yuansong Xu , Yichao Zhu , Haokai Wang , Yuchen Wu , Yang Ouyang , Hanlu Li , Wenzhe Zhou , Xinyu Liu , Chang Jiang , Quan Li

The rapid advancements in large language models (LLMs) have opened up new opportunities for transforming patient engagement in healthcare through conversational AI. This paper presents an overview of the current landscape of LLMs in…

Artificial Intelligence · Computer Science 2024-11-27 Bo Wen , Raquel Norel , Julia Liu , Thaddeus Stappenbeck , Farhana Zulkernine , Huamin Chen

Objective: This paper introduces a patient simulator for scalable, automated evaluation of healthcare conversational agents, generating realistic, controllable interactions that systematically vary across medical, linguistic, and behavioral…

The severe shortage of medical doctors limits access to timely and reliable healthcare, leaving millions underserved. Large language models (LLMs) offer a potential solution but struggle in real-world clinical interactions. Many LLMs are…

Computation and Language · Computer Science 2026-05-11 Jiayuan Zhu , Jiazhen Pan , Yuyuan Liu , Fenglin Liu , Junde Wu

With the advent of Large Language Models (LLMs), medical artificial intelligence (AI) has experienced substantial technological progress and paradigm shifts, highlighting the potential of LLMs to streamline healthcare delivery and improve…

Computation and Language · Computer Science 2024-12-10 Lei Liu , Xiaoyan Yang , Junchi Lei , Yue Shen , Jian Wang , Peng Wei , Zhixuan Chu , Zhan Qin , Kui Ren

Artificial intelligence has significantly advanced healthcare, particularly through large language models (LLMs) that excel in medical question answering benchmarks. However, their real-world clinical application remains limited due to the…

Computation and Language · Computer Science 2024-07-01 Zhihao Fan , Jialong Tang , Wei Chen , Siyuan Wang , Zhongyu Wei , Jun Xi , Fei Huang , Jingren Zhou

Artificial Intelligence (AI) for supporting healthcare services has never been more necessitated than by the recent global pandemic. Here, we review the state-of-the-art in AI-enabled Chatbots in healthcare proposed during the last 10 years…

Artificial Intelligence · Computer Science 2023-08-09 Basabdatta Sen Bhattacharya , Vibhav Sinai Pissurlenkar

Large Language Models (LLMs) have brought huge improvements to Artificial Intelligence (AI), which can be applied to general-purpose tasks. However, their application to textual or spoken medical consultations is still an open research…

Artificial Intelligence · Computer Science 2026-05-27 Heriberto Cuayahuitl , Grace Jang

Online health resources and large language models (LLMs) are increasingly used as a first point of contact for medical decision-making, yet their reliability in healthcare remains limited by low accuracy, lack of transparency, and…

Artificial Intelligence · Computer Science 2026-04-22 Yujia Liu , Sophia Yu , Hongyue Jin , Jessica Wen , Alexander Qian , Terrence Lee , Mattheus Ramsis , Gi Won Choi , Lianhui Qin , Xin Liu , Edward J. Wang

The rise of large language models (LLMs) has transformed healthcare by offering clinical guidance, yet their direct deployment to patients poses safety risks due to limited domain expertise. To mitigate this, we propose repositioning LLMs…

Computation and Language · Computer Science 2025-10-14 Wenya Xie , Qingying Xiao , Yu Zheng , Xidong Wang , Junying Chen , Ke Ji , Anningzhe Gao , Prayag Tiwari , Xiang Wan , Feng Jiang , Benyou Wang

While large language models (LLMs) have shown promise in diagnostic dialogue, their capabilities for effective management reasoning - including disease progression, therapeutic response, and safe medication prescription - remain…

Large Language Models (LLMs) have demonstrated great potential for conducting diagnostic conversations but evaluation has been largely limited to language-only interactions, deviating from the real-world requirements of remote care…

Online, people often recount their experiences turning to conversational AI agents (e.g., ChatGPT, Claude, Copilot) for mental health support -- going so far as to replace their therapists. These anecdotes suggest that AI agents have great…

In this study, we investigate the feasibility of using a human-centered artificial intelligence (AI) chat platform where medical specialists collaboratively assess complex cases. As the target population for this platform, we focus on…

Human-Computer Interaction · Computer Science 2025-03-24 Shinnosuke Sawano , Satoshi Kodera
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