  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.
