human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a short review of ethical challenges in clinical natural language processing"
  Abstract: Clinical NLP has an immense potential in contributing to how clinical practice will be revolutionized by the advent of large scale processing of clinical records. However, this potential has remained largely untapped due to slow progress primarily caused by strict data access policies for researchers. In this paper, we discuss the concern for privacy and the measures it entails. We also suggest sources of less sensitive data. Finally, we draw attention to biases that can compromise the validity of empirical research and lead to socially harmful applications.

Connected through hyperedge HE-1 (induced by source paper "adapting deep learning methods for mental health prediction on social media"):
  with members:
    - "not just depressed bipolar disorder prediction on reddit"
    - "smhd a large scale resource for exploring online language usage for multiple mental health conditions"
    - "revisiting unreasonable effectiveness of data in deep learning era"
    - "multi task learning for mental health using social media text"
    - "detecting and explaining crisis"
    - "depression and self harm risk assessment in online forums"
    - "character level and multi channel convolutional neural networks for large scale authorship attribution"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-2 (induced by source paper "emrqa a large corpus for question answering on electronic medical records"):
  with members:
    - "annotating electronic medical records for question answering"
    - "deep ehr a survey of recent advances in deep learning techniques for electronic health record ehr analysis"
    - "triviaqa a large scale distantly supervised challenge dataset for reading comprehension"
    - "quasar datasets for question answering by search and reading"
    - "question answering with grammatically interpretable representations"
    - "reading wikipedia to answer open domain questions"
    - "newsqa a machine comprehension dataset"
    - "squad 100 000 questions for machine comprehension of text"

Connected through hyperedge HE-3 (induced by source paper "deep ehr a survey of recent advances in deep learning techniques for electronic health record ehr analysis"):
  with members:
    - "medical concept representation learning from electronic health records and its application on heart failure prediction"
    - "bidirectional recurrent neural networks for medical event detection in electronic health records"
    - "de identification of patient notes with recurrent neural networks"
    - "brundlefly at semeval 2016 task 12 recurrent neural networks vs joint inference for clinical temporal information extraction"
    - "structured prediction models for rnn based sequence labeling in clinical text"
    - "recurrent neural networks for multivariate time series with missing values"
    - "doctor ai predicting clinical events via recurrent neural networks"
    - "incremental knowledge base construction using deepdive"

Connected through hyperedge HE-4 (induced by source paper "smhd a large scale resource for exploring online language usage for multiple mental health conditions"):
  with members:
    - "rsdd time temporal annotation of self reported mental health diagnoses"
    - "detecting and explaining crisis"
    - "triaging content severity in online mental health forums"
    - "inferring individual attributes from search engine queries and auxiliary information"
    - "feature studies to inform the classification of depressive symptoms from twitter data for population health"
    - "depression and self harm risk assessment in online forums"
    - "large scale analysis of counseling conversations an application of natural language processing to mental health"
    - "xgboost a scalable tree boosting system"

Connected through hyperedge HE-5 (induced by source paper "depression and self harm risk assessment in online forums"):
  with members:
    - "natural language processing for mental health large scale discourse analysis of counseling conversations"
    - "bag of tricks for efficient text classification"
    - "efficient character level document classification by combining convolution and recurrent layers"
    - "skip thought vectors"
    - "depechemood a lexicon for emotion analysis from crowd annotated news"
    - "adam a method for stochastic optimization"
    - "a convolutional neural network for modelling sentences"

Question: Please tell me which class the center node 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.CL(Computation and Language)