human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "chexplain enabling physicians to explore and understanddata driven ai enabled medical imaging analysis"):
  Abstract: The recent development of data-driven AI promises to automate medical diagnosis; however, most AI functions as 'black boxes' to physicians with limited computational knowledge. Using medical imaging as a point of departure, we conducted three iterations of design activities to formulate CheXplain---a system that enables physicians to explore and understand AI-enabled chest X-ray analysis: (1) a paired survey between referring physicians and radiologists reveals whether, when, and what kinds of explanations are needed; (2) a low-fidelity prototype co-designed with three physicians formulates eight key features; and (3) a high-fidelity prototype evaluated by another six physicians provides detailed summative insights on how each feature enables the exploration and understanding of AI. We summarize by discussing recommendations for future work to design and implement explainable medical AI systems that encompass four recurring themes: motivation, constraint, explanation, and justification.

Includes members:
  Member "outlining the design space of explainable intelligent systems for medical diagnosis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on explainable artificial intelligence xai towards medical xai")
  Member "human centered tools for coping with imperfect algorithms during medical decision making":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "explainer a visual analytics framework for interactive and explainable machine learning")
  Member "explanation methods in deep learning users values concerns and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "explainable cardiac pathology classification on cine mri with motion characterization by semi supervised learning of apparent flow":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "foal fast online adaptive learning for cardiac motion estimation")
  Member "explanations based on the missing towards contrastive explanations with pertinent negatives":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "generating counterfactual explanations with natural language":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "causal interpretability for machine learning problems methods and evaluation")
  Member "towards interpretable r cnn by unfolding latent structures":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "towards a unified evaluation of explanation methods without ground truth")
  Member "explanation in artificial intelligence insights from the social sciences":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "causal interpretability for machine learning problems methods and evaluation")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.HC(Human-Computer Interaction)