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 novel hybrid machine learning model for auto classification of retinal diseases"
  Abstract: Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. We propose a novel visual-assisted diagnosis hybrid model based on the support vector machine (SVM) and deep neural networks (DNNs). The model incorporates complementary strengths of DNNs and SVM. Furthermore, we present a new clinical retina label collection for ophthalmology incorporating 32 retina diseases classes. Using EyeNet, our model achieves 89.73% diagnosis accuracy and the model performance is comparable to the professional ophthalmologists.

Connected through hyperedge HE-1 (induced by source paper "synthesizing new retinal symptom images by multiple generative models"):
  with members:
    - "a closed form solution to photorealistic image stylization"
    - "high resolution medical image synthesis using progressively grown generative adversarial networks"
    - "auto classification of retinal diseases in the limit of sparse data using a two streams machine learning model"
    - "ganimation anatomically aware facial animation from a single image"
    - "chestx ray8 hospital scale chest x ray database and benchmarks on weakly supervised classification and localization of common thorax diseases"
    - "deep photo style transfer"
    - "pose normalized image generation for person re identification"
    - "synthetic medical images from dual generative adversarial networks"

Connected through hyperedge HE-2 (induced by source paper "auto classification of retinal diseases in the limit of sparse data using a two streams machine learning model"):
  with members:
    - "cardiologist level arrhythmia detection with convolutional neural networks"
    - "chexnet radiologist level pneumonia detection on chest x rays with deep learning"
    - "a novel framework for robustness analysis of visual qa models"
    - "chestx ray8 hospital scale chest x ray database and benchmarks on weakly supervised classification and localization of common thorax diseases"
    - "radnet radiologist level accuracy using deep learning for hemorrhage detection in ct scans"
    - "vqabq visual question answering by basic questions"
    - "robustness analysis of visual qa models by basic questions"
    - "superimposition of eye fundus images for longitudinal analysis from large public health databases"

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.CV(Computer Vision and Pattern Recognition)