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: "fused segmentation of geometric models for myocardium and coronary artery via medial axis"
  Abstract: Coronary arteries and their branches supply blood to myocardium. The obstruction of coronary arteries results in significant loss of myocardium, called acute myocardial infarction, and the number one cause of death globally. Hence, quantification of the regional amount of heart muscle subtended by obstructed coronary arteries is of critical value in clinical medicine. However, the conventional methods are inaccurate and frequently disagree with clinical practices. This study proposes a novel algorithm to segment regional myocardium-at-risk subtended by any potentially obstructed coronary artery. Assuming the geometric triangular mesh models of coronary artery and myocardium derived from an individual cardiac computed tomography image, the proposed algorithm performs (i) computation of the medial axis of the coronary artery and (ii) segmentation of the coronary artery and myocardium using the medial axis. The algorithm provides the fused segmentation of coronary artery and myocardium via the medial axis. The computed result provides a robust mathematical linkage between myocardium-at-risk and supplying coronary arteries so that ischemic myocardial regions can be accurately identified, and both the extent and severity of myocardial ischemia can be quantified effectively and efficiently. Furthermore, the correspondence between segmented coronary artery and myocardium can be more importantly used for building optimization models of cardiac systems for various applications. We believe that the proposed algorithm and implemented VoroHeart program, which is freely available at this http URL, will be an invaluable tool for patient-specific risk predictions and the treatment of obstructed coronary artery disease in clinical medicine. The algorithmic accuracy and efficiency are theoretically asserted and experimentally verified.

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.CG(Computational Geometry)