AIvsClinician: Unveiling Intricate Interactions Between AI and Clinicians through an Open-Access Database
<|reference_start|>AIvsClinician: Unveiling Intricate Interactions Between AI and Clinicians through an Open-Access Database: Artificial Intelligence (AI) plays a crucial role in medical field and has the potential to revolutionize healthcare practices. However, the success of AI models and their impacts hinge on the synergy between AI and medical specialists, with clinicians assuming a dominant role. Unfortunately, the intricate dynamics and interactions between AI and clinicians remain undiscovered and thus hinder AI from being translated into medical practice. To address this gap, we have curated a groundbreaking database called AI.vs.Clinician. This database is the first of its kind for studying the interactions between AI and clinicians. It derives from 7,500 collaborative diagnosis records on a life-threatening medical emergency -- Sepsis -- from 14 medical centers across China. For the patient cohorts well-chosen from MIMIC databases, the AI-related information comprises the model property, feature input, diagnosis decision, and inferred probabilities of sepsis onset presently and within next three hours. The clinician-related information includes the viewed examination data and sequence, viewed time, preliminary and final diagnosis decisions with or without AI assistance, and recommended treatment.<|reference_end|>
@article{gao2024ai.vs.clinician:,
    title={AI.vs.Clinician: Unveiling Intricate Interactions Between AI and
  Clinicians through an Open-Access Database},
    author={Wanling Gao and Yuan Liu and Zhuoming Yu and Dandan Cui and Wenjing
  Liu and Xiaoshuang Liang and Jiahui Zhao and Jiyue Xie and Hao Li and Li Ma
  and Ning Ye and Yumiao Kang and Dingfeng Luo and Peng Pan and Wei Huang and
  Zhongmou Liu and Jizhong Hu and Fan Huang and Gangyuan Zhao and Chongrong
  Jiang and Tianyi Wei and Zhifei Zhang and Yunyou Huang and Jianfeng Zhan},
    journal={arXiv preprint arXiv:2406.07362},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.07362},
    primaryClass={cs.HC}
}