Community Detection Algorithms in Healthcare Applications: A Systematic Review

Over the past few years, the number and volume of data sources in healthcare databases has grown exponentially. Analyzing these voluminous medical data is both opportunity and challenge for knowledge discovery in health informatics. In the last decade, social network analysis techniques and community detection algorithms are being used more and more in scientific fields, including healthcare and medicine. While community detection algorithms have been widely used for social network analysis, a comprehensive review of its applications for healthcare in a way to benefit both health practitioners and the health informatics community is still overwhelmingly missing. This paper contributes to fill in this gap and provide a comprehensive and up-to-date literature research. Especially, categorizations of existing community detection algorithms are presented and discussed. Moreover, most applications of social network analysis and community detection algorithms in healthcare are reviewed and categorized. Finally, publicly available healthcare datasets, key challenges, and knowledge gaps in the field are studied and reviewed.

[1]  Daoqiang Zhang,et al.  Multi-Modal Non-Euclidean Brain Network Analysis With Community Detection and Convolutional Autoencoder , 2023, IEEE Transactions on Emerging Topics in Computational Intelligence.

[2]  Yue Xu,et al.  Graph Regularized Nonnegative Matrix Factorization for Community Detection in Attributed Networks , 2023, IEEE Transactions on Network Science and Engineering.

[3]  S. Gorgin,et al.  A new energy-efficient and temperature-aware routing protocol based on fuzzy logic for multi-WBANs , 2022, Ad Hoc Networks.

[4]  Philip S. Yu,et al.  A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning , 2021, IEEE Transactions on Knowledge and Data Engineering.

[5]  Dong Liu,et al.  How to Protect Ourselves From Overlapping Community Detection in Social Networks , 2022, IEEE Transactions on Big Data.

[6]  S. Dhingra,et al.  The Use of Artificial Intelligence in Pharmacovigilance: A Systematic Review of the Literature , 2022, Pharmaceutical Medicine.

[7]  P. Moradi,et al.  Graph-based relevancy-redundancy gene selection method for cancer diagnosis , 2022, Comput. Biol. Medicine.

[8]  V. Moscato,et al.  Community detection over feature-rich information networks: An eHealth case study , 2022, Inf. Syst..

[9]  V. Leve,et al.  Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations , 2022, BMC Health Services Research.

[10]  Xiang Fei,et al.  A Survey of Community Detection in Complex Networks Using Nonnegative Matrix Factorization , 2022, IEEE Transactions on Computational Social Systems.

[11]  Zbigniew Leonowicz,et al.  A Social Network Analysis Approach to COVID-19 Community Detection Techniques , 2022, International journal of environmental research and public health.

[12]  Richard F. Betzel,et al.  Social cognitive network neuroscience , 2022, Social cognitive and affective neuroscience.

[13]  Lindsay E. Young,et al.  Social Media Communication and Network Correlates of HIV Infection and Transmission Risks Among Black Sexual Minority Men: Cross-sectional Digital Epidemiology Study , 2022, JMIR formative research.

[14]  Ruiqi Hu,et al.  Deep neighbor-aware embedding for node clustering in attributed graphs , 2022, Pattern Recognit..

[15]  Alina Peluso,et al.  Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients , 2022, PloS one.

[16]  Rachid Jennane,et al.  A complex network based approach for knee Osteoarthritis detection: Data from the Osteoarthritis initiative , 2022, Biomed. Signal Process. Control..

[17]  Guanxiong Huang,et al.  Core social network size is associated with physical activity participation for fitness app users: The role of social comparison and social support , 2021, Comput. Hum. Behav..

[18]  Saman Forouzandeh,et al.  Gene selection for microarray data classification via multi-objective graph theoretic-based method , 2021, Artif. Intell. Medicine.

[19]  Quan Z. Sheng,et al.  A Comprehensive Survey on Community Detection With Deep Learning , 2021, IEEE Transactions on Neural Networks and Learning Systems.

[20]  Clair A. Kronk,et al.  Transgender data collection in the electronic health record: Current concepts and issues , 2021, J. Am. Medical Informatics Assoc..

[21]  J. Stroebel,et al.  JUE Insight: The geographic spread of COVID-19 correlates with the structure of social networks as measured by Facebook , 2021, Journal of Urban Economics.

[22]  Xiangrong Wang,et al.  Efficient Algorithm Based on Non-Backtracking Matrix for Community Detection in Signed Networks , 2020, IEEE Transactions on Network Science and Engineering.

[23]  Kazuya Shimizu,et al.  Exponential-Time Quantum Algorithms for Graph Coloring Problems , 2019, Algorithmica.

[24]  Ita Richardson,et al.  Blockchain-Based Identity Management Systems in Health IoT: A Systematic Review , 2022, IEEE Access.

[25]  Luwen Shi,et al.  Review of social networks of professionals in healthcare settings—where are we and what else is needed? , 2021, Globalization and Health.

[26]  Rojiar Pir Mohammadiani,et al.  A novel method of spectral clustering in attributed networks by constructing parameter-free affinity matrix , 2021, Cluster Computing.

[27]  Saeid Nahavandi,et al.  A novel deep neuroevolution-based image classification method to diagnose coronavirus disease (COVID-19) , 2021, Computers in Biology and Medicine.

[28]  Omar N. Elayan,et al.  Regional analytics and forecasting for most affected stock markets: The case of GCC stock markets during COVID-19 pandemic , 2021, International Journal of System Assurance Engineering and Management.

[29]  Jonathan H. Chen,et al.  Deep learning evaluation of biomarkers from echocardiogram videos , 2021, EBioMedicine.

[30]  Rojiar Pir Mohammadiani,et al.  Spectral clustering on protein-protein interaction networks via constructing affinity matrix using attributed graph embedding , 2021, Comput. Biol. Medicine.

[31]  Jianhua Li,et al.  Unsupervised learning for community detection in attributed networks based on graph convolutional network , 2021, Neurocomputing.

[32]  Hocine Cherifi,et al.  Extracting modular-based backbones in weighted networks , 2021, Inf. Sci..

[33]  Fabio Giampaolo,et al.  Artificial intelligence and healthcare: Forecasting of medical bookings through multi-source time-series fusion , 2021, Inf. Fusion.

[34]  P. Lemey,et al.  A systematic review on global RSV genetic data: Identification of knowledge gaps , 2021, Reviews in Medical Virology.

[35]  Xueshuo Xie,et al.  AWAP: Adaptive weighted attribute propagation enhanced community detection model for bitcoin de-anonymization , 2021, Appl. Soft Comput..

[36]  Carlos Hoppen,et al.  Balanced portfolio via signed graphs and spectral clustering in the Brazilian stock market , 2021, Quality & Quantity.

[37]  Michael Gadermayr,et al.  Anomaly Detection in Medical Imaging - A Mini Review , 2021, ArXiv.

[38]  Minglong Lei,et al.  Deep attributed graph clustering with self-separation regularization and parameter-free cluster estimation , 2021, Neural Networks.

[39]  S. Nahavandi,et al.  An oppositional-Cauchy based GSK evolutionary algorithm with a novel deep ensemble reinforcement learning strategy for COVID-19 diagnosis , 2021, Applied Soft Computing.

[40]  F. Schwendicke,et al.  Data Dentistry: How Data Are Changing Clinical Care and Research , 2021, Journal of dental research.

[41]  Mohammed A. A. Al-qaness,et al.  Social Media Toxicity Classification Using Deep Learning: Real-World Application UK Brexit , 2021, Electronics.

[42]  Tansel Dökeroglu,et al.  Memetic Teaching-Learning-Based Optimization algorithms for large graph coloring problems , 2021, Eng. Appl. Artif. Intell..

[43]  M. Gurcan,et al.  Deep learning predicts gene expression as an intermediate data modality to identify susceptibility patterns in Mycobacterium tuberculosis infected Diversity Outbred mice , 2021, EBioMedicine.

[44]  M. You,et al.  A social network analysis of the spread of COVID-19 in South Korea and policy implications , 2021, Scientific Reports.

[45]  Clara Pizzuti,et al.  A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions , 2021, Swarm Evol. Comput..

[46]  Laihang Yu,et al.  Application of network link prediction in drug discovery , 2021, BMC Bioinformatics.

[47]  Pan Peng,et al.  Mixed-order spectral clustering for complex networks , 2021, Pattern Recognit..

[48]  Putra Sumari, Saqib Jamal Syed, Laith Abualigah,et al.  A Novel Deep Learning Pipeline Architecture based on CNN to Detect Covid-19 in Chest X-ray Images , 2021, Turkish Journal of Computer and Mathematics Education (TURCOMAT).

[49]  Meizi Li,et al.  A Community Detection Method for Social Network Based on Community Embedding , 2021, IEEE Transactions on Computational Social Systems.

[50]  Kai Lei,et al.  Dual-channel hybrid community detection in attributed networks , 2021, Inf. Sci..

[51]  Junhui Wang,et al.  Community Detection in General Hypergraph Via Graph Embedding , 2021, Journal of the American Statistical Association.

[52]  E. Pérez-Rueda,et al.  A landscape for drug-target interactions based on network analysis , 2021, PloS one.

[53]  Debarka Sengupta,et al.  Hide and Seek: Outwitting Community Detection Algorithms , 2021, IEEE Transactions on Computational Social Systems.

[54]  Xueyan Liu,et al.  Interpretable Variational Graph Autoencoder with Noninformative Prior , 2021, Future Internet.

[55]  Isa Inuwa-Dutse,et al.  A multilevel clustering technique for community detection , 2021, Neurocomputing.

[56]  Shengli Zhang,et al.  Community Detection in Blockchain Social Networks , 2021, J. Commun. Inf. Networks.

[57]  E. Steultjens,et al.  The role of the social network during inpatient rehabilitation: A qualitative study exploring the views of older stroke survivors and their informal caregivers , 2021, Topics in stroke rehabilitation.

[58]  Xingwang Zhao,et al.  A community detection algorithm based on graph compression for large-scale social networks , 2020, Inf. Sci..

[59]  Mehrdad Rostami,et al.  A novel community detection based genetic algorithm for feature selection , 2020, Journal of Big Data.

[60]  Timothy C. Havens,et al.  Soft Overlapping Community Detection in Large-Scale Networks via Fast Fuzzy Modularity Maximization , 2020, IEEE Transactions on Fuzzy Systems.

[61]  Hadi Zare,et al.  Detection of Community Structures in Networks With Nodal Features based on Generative Probabilistic Approach , 2019, IEEE Transactions on Knowledge and Data Engineering.

[62]  P. Raghavendra,et al.  Local Statistics, Semidefinite Programming, and Community Detection , 2019, SODA.

[63]  Olivier Goudet,et al.  Population-based gradient descent weight learning for graph coloring problems , 2019, Knowl. Based Syst..

[64]  Z. Caner Taskin,et al.  An Exact Cutting Plane Algorithm to Solve the Selective Graph Coloring Problem in Perfect Graphs , 2018, Eur. J. Oper. Res..

[65]  Mingchen Li,et al.  DynaMo: Dynamic Community Detection by Incrementally Maximizing Modularity , 2017, IEEE Transactions on Knowledge and Data Engineering.

[66]  Hocine Cherifi,et al.  Complex Network and Source Inspired COVID-19 Fake News Classification on Twitter , 2021, IEEE Access.

[67]  Shing Chiang Tan,et al.  A Review on Community Detection in Large Complex Networks from Conventional to Deep Learning Methods: A Call for the Use of Parallel Meta-Heuristic Algorithms , 2021, IEEE Access.

[68]  Vincenzo Moscato,et al.  A survey about community detection over On-line Social and Heterogeneous Information Networks , 2021, Knowl. Based Syst..

[69]  Eatedal Alabdulkreem,et al.  Detection of Community Structures in Dynamic Social Networks Based on Message Distribution and Structural/Attribute Similarities , 2021, IEEE Access.

[70]  Tongrang Fan,et al.  Analyzing and visualizing scientific research collaboration network with core node evaluation and community detection based on network embedding , 2021, Pattern Recognit. Lett..

[71]  Wenbin Yao,et al.  Deep Attributed Network Embedding with Community Information , 2021, MMM.

[72]  Zhan Bu,et al.  Proximity-based group formation game model for community detection in social network , 2021, Knowl. Based Syst..

[73]  Xiangqian Ding,et al.  Health level classification by fusing medical evaluation from multiple social networks , 2021, Future Gener. Comput. Syst..

[74]  Muhammad Attique,et al.  An intelligent healthcare monitoring framework using wearable sensors and social networking data , 2021, Future Gener. Comput. Syst..

[75]  Stephen A. Rains,et al.  Social Enhancement and Compensation in Online Social Support among Cancer Patients: The Role of Social Network Properties , 2020, Health communication.

[76]  A. Amanatidou,et al.  Construction and Analysis of Protein-Protein Interaction Network of Non-Alcoholic Fatty Liver Disease , 2020, bioRxiv.

[77]  Clara Pizzuti,et al.  Multiobjective Optimization and Local Merge for Clustering Attributed Graphs , 2020, IEEE Transactions on Cybernetics.

[78]  Jiawei Zhang,et al.  CommDGI: Community Detection Oriented Deep Graph Infomax , 2020, CIKM.

[79]  Sanjay Kumar,et al.  Identifying influential nodes in Social Networks: Neighborhood Coreness based voting approach , 2020, Physica A: Statistical Mechanics and its Applications.

[80]  Philip S. Yu,et al.  SEAL: Learning Heuristics for Community Detection with Generative Adversarial Networks , 2020, KDD.

[81]  Xiaochun Cao,et al.  JANE: Jointly Adversarial Network Embedding , 2020, IJCAI.

[82]  Amir Albadvi,et al.  A New Application of Louvain Algorithm for Identifying Disease Fields Using Big Data Techniques , 2020, Journal of Biostatistics and Epidemiology.

[83]  H. Bustince,et al.  Community detection and Social Network analysis based on the Italian wars of the 15th century , 2020, Future Gener. Comput. Syst..

[84]  Yun Zhang,et al.  LILPA: A label importance based label propagation algorithm for community detection with application to core drug discovery , 2020, Neurocomputing.

[85]  Xiaoxiong Zhong,et al.  Detecting community in attributed networks by dynamically exploring node attributes and topological structure , 2020, Knowl. Based Syst..

[86]  Yang Li,et al.  Network Embedding for Community Detection in Attributed Networks , 2020, ACM Trans. Knowl. Discov. Data.

[87]  Xin Wang,et al.  Community detection based on first passage probabilities , 2020, ArXiv.

[88]  Babak Teimourpour,et al.  A new application of community detection for identifying the real specialty of physicians , 2020, Int. J. Medical Informatics.

[89]  Fang Hu,et al.  Community detection in complex networks using Node2vec with spectral clustering , 2020, Physica A: Statistical Mechanics and its Applications.

[90]  Frédéric Ros,et al.  Texture Analysis and Genetic Algorithms for Osteoporosis Diagnosis , 2020, Int. J. Pattern Recognit. Artif. Intell..

[91]  Aladine Chetouani,et al.  Discriminative Regularized Auto-Encoder for Early Detection of Knee OsteoArthritis: Data from the Osteoarthritis Initiative , 2020, IEEE Transactions on Medical Imaging.

[92]  Maoguo Gong,et al.  Preventing epidemic spreading in networks by community detection and memetic algorithm , 2020, Appl. Soft Comput..

[93]  K. Blanchet,et al.  Professional advice for primary healthcare workers in Ethiopia: a social network analysis , 2020, BMC Health Services Research.

[94]  Yuanyuan Wang,et al.  Spectral clustering-based community detection using graph distance and node attributes , 2019, Computational Statistics.

[95]  Erik Cambria,et al.  The Four Dimensions of Social Network Analysis: An Overview of Research Methods, Applications, and Software Tools , 2020, Inf. Fusion.

[96]  Irwin King,et al.  MAGNN: Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding , 2020, WWW.

[97]  Petr Chunaev,et al.  Community detection in node-attributed social networks: a survey , 2019, Comput. Sci. Rev..

[98]  Jerome Niyirora,et al.  Network analysis of medical care services , 2019, Health Informatics J..

[99]  Jiawei Han,et al.  Unsupervised Attributed Multiplex Network Embedding , 2019, AAAI.

[100]  Ryan A. Rossi,et al.  On Proximity and Structural Role-based Embeddings in Networks , 2019, ACM Trans. Knowl. Discov. Data.

[101]  Fu-Lai Chung,et al.  Deep Network Embedding for Graph Representation Learning in Signed Networks , 2019, IEEE Transactions on Cybernetics.

[102]  Biswanath Dutta,et al.  Weighted kshell degree neighborhood: A new method for identifying the influential spreaders from a variety of complex network connectivity structures , 2020, Expert Syst. Appl..

[103]  S. Kalkman,et al.  Patients’ and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence , 2019, Journal of Medical Ethics.

[104]  Saeid Nahavandi,et al.  An efficient Neuroevolution Approach for Heart Disease Detection , 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).

[105]  Jie Hu,et al.  Community detection based on human social behavior , 2019, Physica A: Statistical Mechanics and its Applications.

[106]  Denny Yu,et al.  Impact of care provider network characteristics on patient outcomes: Usage of social network analysis and a multi-scale community detection , 2019, PloS one.

[107]  Dapeng Wu,et al.  Game Theoretical Approach for Non-Overlapping Community Detection , 2019, 2019 5th International Conference on Big Data Computing and Communications (BIGCOM).

[108]  Weixiong Zhang,et al.  Network-Specific Variational Auto-Encoder for Embedding in Attribute Networks , 2019, IJCAI.

[109]  Ying Xie,et al.  High-performance community detection in social networks using a deep transitive autoencoder , 2019, Inf. Sci..

[110]  Jian Pei,et al.  ProGAN: Network Embedding via Proximity Generative Adversarial Network , 2019, KDD.

[111]  Weixiong Zhang,et al.  Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks , 2019, AAAI.

[112]  Xiaotong Zhang,et al.  Attributed Graph Clustering via Adaptive Graph Convolution , 2019, IJCAI.

[113]  Jing Jiang,et al.  Attributed Graph Clustering: A Deep Attentional Embedding Approach , 2019, IJCAI.

[114]  E. Lespessailles,et al.  A decision support tool for early detection of knee OsteoArthritis using X-ray imaging and machine learning: Data from the OsteoArthritis Initiative , 2019, Comput. Medical Imaging Graph..

[115]  M. Sepehri,et al.  Community detection in attributed networks considering both structural and attribute similarities: two mathematical programming approaches , 2019, Neural Computing and Applications.

[116]  Xinbing Wang,et al.  CommunityGAN: Community Detection with Generative Adversarial Nets , 2019, WWW.

[117]  Rachel C. Shelton,et al.  Use of social network analysis in the development, dissemination, implementation, and sustainability of health behavior interventions for adults: A systematic review. , 2019, Social science & medicine.

[118]  Asgarali Bouyer,et al.  A Link-Based Similarity for Improving Community Detection Based on Label Propagation Algorithm , 2018, Journal of Systems Science and Complexity.

[119]  Vincent A. Traag,et al.  From Louvain to Leiden: guaranteeing well-connected communities , 2018, Scientific Reports.

[120]  Stephan Günnemann,et al.  Overlapping Community Detection with Graph Neural Networks , 2018, ArXiv.

[121]  Sreeram Kannan,et al.  ClusterGAN : Latent Space Clustering in Generative Adversarial Networks , 2018, AAAI.

[122]  Thibaut Jombart,et al.  A graph-based evidence synthesis approach to detecting outbreak clusters: An application to dog rabies , 2018, PLoS Comput. Biol..

[123]  Naiyang Guan,et al.  Graph Regularized Symmetric Non-Negative Matrix Factorization for Graph Clustering , 2018, 2018 IEEE International Conference on Data Mining Workshops (ICDMW).

[124]  David Camacho,et al.  A new algorithm for communities detection in social networks with node attributes , 2018, J. Ambient Intell. Humaniz. Comput..

[125]  Philip S. Yu,et al.  Parallel Protein Community Detection in Large-scale PPI Networks Based on Multi-source Learning , 2018, IEEE/ACM transactions on computational biology and bioinformatics.

[126]  Sancho Salcedo-Sanz,et al.  A Multi-Objective Genetic Algorithm for overlapping community detection based on edge encoding , 2018, Inf. Sci..

[127]  Jianwu Dang,et al.  Incorporating network structure with node contents for community detection on large networks using deep learning , 2018, Neurocomputing.

[128]  K. de la Haye,et al.  Applications of social network analysis to obesity: a systematic review , 2018, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[129]  Felix Gräßer,et al.  Aspect-Based Sentiment Analysis of Drug Reviews Applying Cross-Domain and Cross-Data Learning , 2018, DH.

[130]  Siddique Latif,et al.  Community detection in networks: A multidisciplinary review , 2018, J. Netw. Comput. Appl..

[131]  Eilish McAuliffe,et al.  Social Network Analysis as a Methodological Approach to Explore Health Systems: A Case Study Exploring Support among Senior Managers/Executives in a Hospital Network , 2018, International journal of environmental research and public health.

[132]  Penelope Sanderson,et al.  Applying social network analysis to the examination of interruptions in healthcare. , 2018, Applied ergonomics.

[133]  Weimin Li,et al.  Overlap community detection using spectral algorithm based on node convergence degree , 2018, Future Gener. Comput. Syst..

[134]  Asgarali Bouyer,et al.  LP-LPA: A link influence-based label propagation algorithm for discovering community structures in networks , 2017 .

[135]  H. Stanley,et al.  The science of science: from the perspective of complex systems , 2017 .

[136]  Philip S. Yu,et al.  BL-MNE: Emerging Heterogeneous Social Network Embedding Through Broad Learning with Aligned Autoencoder , 2017, 2017 IEEE International Conference on Data Mining (ICDM).

[137]  K. Blanchet,et al.  Use of social network analysis methods to study professional advice and performance among healthcare providers: a systematic review , 2017, Systematic Reviews.

[138]  A. Gaudin,et al.  Hospitalisation costs of metastatic melanoma in France; the MELISSA study (MELanoma In hoSpital coSts Assessment) , 2017, BMC Health Services Research.

[139]  Peixiang Zhao,et al.  Attributed Graph Clustering: an Attribute-aware Graph Embedding Approach , 2017, ASONAM.

[140]  Katarzyna Musial,et al.  Adaptive Community Detection Incorporating Topology and Content in Social Networks , 2017, 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[141]  Feng Liu,et al.  Joint Weighted Nonnegative Matrix Factorization for Mining Attributed Graphs , 2017, PAKDD.

[142]  Alessio Conte,et al.  Efficiently Clustering Very Large Attributed Graphs , 2017, 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[143]  Xin Xin,et al.  Deep community detection in topologically incomplete networks , 2017 .

[144]  Nilanjan Dey,et al.  Internet of Things and Big Data Technologies for Next Generation Healthcare , 2017 .

[145]  B Balamurugan,et al.  Social Network Analysis in Healthcare , 2017 .

[146]  Eduardo Bezerra,et al.  Discovering top-k non-redundant clusterings in attributed graphs , 2016, Neurocomputing.

[147]  Li Pan,et al.  Multi-objective community detection method by integrating users' behavior attributes , 2016, Neurocomputing.

[148]  Ming Wen,et al.  Building a National Neighborhood Dataset From Geotagged Twitter Data for Indicators of Happiness, Diet, and Physical Activity , 2016, JMIR public health and surveillance.

[149]  Xiao Zhi Gao,et al.  Graph clustering using k-Neighbourhood Attribute Structural similarity , 2016, Appl. Soft Comput..

[150]  C. Viboud,et al.  Mathematical models to characterize early epidemic growth: A review. , 2016, Physics of life reviews.

[151]  Weidi Dai,et al.  A multi-similarity spectral clustering method for community detection in dynamic networks , 2016, Scientific Reports.

[152]  Xiaochun Cao,et al.  Modularity Based Community Detection with Deep Learning , 2016, IJCAI.

[153]  Wei Wang,et al.  Detecting Overlapping Community Structures with PCA Technology and Member Index , 2016, MobiMedia.

[154]  Song Chen,et al.  Health Care Fraud Detection with Community Detection Algorithms , 2016, 2016 IEEE International Conference on Smart Computing (SMARTCOMP).

[155]  Peter Szolovits,et al.  MIMIC-III, a freely accessible critical care database , 2016, Scientific Data.

[156]  Xiaochun Cao,et al.  Semantic Community Identification in Large Attribute Networks , 2016, AAAI.

[157]  Sreekanth Rallapalli,et al.  Cloud Based K-Means Clustering Running as a MapReduce Job for Big Data Healthcare Analytics Using Apache Mahout , 2016 .

[158]  Hongtao Lu,et al.  Community detection in social network with pairwisely constrained symmetric non-negative matrix factorization , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[159]  Zhang Zhen,et al.  Identifying the Communities in the Metabolic Network Using 'Component' Definition and Girvan-Newman Algorithm , 2015, 2015 14th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES).

[160]  Lin Wang,et al.  Coupled disease–behavior dynamics on complex networks: A review , 2015, Physics of Life Reviews.

[161]  Ramzi A. Haraty,et al.  An Enhanced k-Means Clustering Algorithm for Pattern Discovery in Healthcare Data , 2015, Int. J. Distributed Sens. Networks.

[162]  Jure Leskovec,et al.  Tensor Spectral Clustering for Partitioning Higher-order Network Structures , 2015, SDM.

[163]  Lili Zhang,et al.  An Efficient Hierarchy Algorithm for Community Detection in Complex Networks , 2014 .

[164]  Emmanuel Müller,et al.  Focused clustering and outlier detection in large attributed graphs , 2014, KDD.

[165]  Lei Li,et al.  Extremal optimization-based semi-supervised algorithm with conflict pairwise constraints for community detection , 2014, 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014).

[166]  Jie Liu,et al.  Novel heuristic density-based method for community detection in networks , 2014 .

[167]  Santo Fortunato,et al.  Community detection in networks: Structural communities versus ground truth , 2014, Physical review. E, Statistical, nonlinear, and soft matter physics.

[168]  Boleslaw K. Szymanski,et al.  Community Detection via Maximization of Modularity and Its Variants , 2014, IEEE Transactions on Computational Social Systems.

[169]  Jing Liu,et al.  A Multiobjective Evolutionary Algorithm Based on Similarity for Community Detection From Signed Social Networks , 2014, IEEE Transactions on Cybernetics.

[170]  Dongxiao He,et al.  Link Community Detection Using Generative Model and Nonnegative Matrix Factorization , 2014, PloS one.

[171]  Jure Leskovec,et al.  Community Detection in Networks with Node Attributes , 2013, 2013 IEEE 13th International Conference on Data Mining.

[172]  Wei Liu,et al.  Community detection in disease-gene network based on principal component analysis , 2013 .

[173]  Ling Liu,et al.  Social influence based clustering of heterogeneous information networks , 2013, KDD.

[174]  Megha Agrawal,et al.  Characterizing Geographic Variation in Well-Being Using Tweets , 2013, ICWSM.

[175]  Srinivasan Parthasarathy,et al.  Efficient community detection in large networks using content and links , 2012, WWW.

[176]  Duncan Chambers,et al.  Social Network Analysis in Healthcare Settings: A Systematic Scoping Review , 2012, PloS one.

[177]  Qingfu Zhang,et al.  Community detection in networks by using multiobjective evolutionary algorithm with decomposition , 2012 .

[178]  Kadim Tasdemir,et al.  Vector quantization based approximate spectral clustering of large datasets , 2012, Pattern Recognit..

[179]  Hong Cheng,et al.  A model-based approach to attributed graph clustering , 2012, SIGMOD Conference.

[180]  Chris H. Q. Ding,et al.  Symmetric Nonnegative Matrix Factorization for Graph Clustering , 2012, SDM.

[181]  Hans-Peter Kriegel,et al.  Density-based community detection in social networks , 2011, 2011 IEEE 5th International Conference on Internet Multimedia Systems Architecture and Application.

[182]  Maoguo Gong,et al.  Memetic algorithm for community detection in networks. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[183]  Fei Wang,et al.  Community discovery using nonnegative matrix factorization , 2011, Data Mining and Knowledge Discovery.

[184]  Jiawei Han,et al.  gSkeletonClu: Density-Based Network Clustering via Structure-Connected Tree Division or Agglomeration , 2010, 2010 IEEE International Conference on Data Mining.

[185]  Jian Liu,et al.  Detecting community structure in complex networks using simulated annealing with k-means algorithms , 2010 .

[186]  Luis Russo,et al.  Who shall survive?: Foundations of sociometry group psychotherapy and sociodrama , 2010 .

[187]  Steve Gregory,et al.  Finding overlapping communities in networks by label propagation , 2009, ArXiv.

[188]  Hong Cheng,et al.  Graph Clustering Based on Structural/Attribute Similarities , 2009, Proc. VLDB Endow..

[189]  Yun Chi,et al.  Combining link and content for community detection: a discriminative approach , 2009, KDD.

[190]  Mathieu Bastian,et al.  Gephi: An Open Source Software for Exploring and Manipulating Networks , 2009, ICWSM.

[191]  G. Bloom,et al.  Future health systems: Why future? Why now? , 2008, Social science & medicine.

[192]  Martin Rosvall,et al.  Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.

[193]  Aric Hagberg,et al.  Exploring Network Structure, Dynamics, and Function using NetworkX , 2008, Proceedings of the Python in Science Conference.

[194]  Myra Spiliopoulou,et al.  Logic Programming to Address Issues of the Semantic Web , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

[195]  Réka Albert,et al.  Near linear time algorithm to detect community structures in large-scale networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[196]  Christos Faloutsos,et al.  Fast Random Walk with Restart and Its Applications , 2006, Sixth International Conference on Data Mining (ICDM'06).

[197]  Mohand-Said Hacid,et al.  A New Clustering Approach for Symbolic Data and Its Validation: Application to the Healthcare Data , 2006, ISMIS.

[198]  Pearl Brereton,et al.  Performing systematic literature reviews in software engineering , 2006, ICSE.

[199]  J. Reichardt,et al.  Statistical mechanics of community detection. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[200]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[201]  Matthieu Latapy,et al.  Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..

[202]  C. Webb,et al.  A network perspective on modularity and control of flow in robust systems , 2006 .

[203]  T. Petty,et al.  Lung cancer detection in patients with airflow obstruction identified in a primary care outpatient practice. , 2005, Chest.

[204]  Jonathan M. Garibaldi,et al.  A COMPARISON OF FUZZY AND NON-FUZZY CLUSTERING TECHNIQUES IN CANCER DIAGNOSIS , 2005 .

[205]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[206]  R. Guimerà,et al.  Modularity from fluctuations in random graphs and complex networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[207]  V. Latora,et al.  Method to find community structures based on information centrality. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[208]  J. Reichardt,et al.  Detecting fuzzy community structures in complex networks with a Potts model. , 2004, Physical review letters.

[209]  M. Newman Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[210]  Claudio Castellano,et al.  Defining and identifying communities in networks. , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[211]  Stefan Boettcher,et al.  Optimization with Extremal Dynamics , 2000, Complex..

[212]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[213]  S. Wasserman,et al.  Social support and social networks: synthesis and review , 2002 .

[214]  Stefan Boettcher,et al.  Extremal Optimization for Graph Partitioning , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[215]  Jianbo Shi,et al.  A Random Walks View of Spectral Segmentation , 2001, AISTATS.

[216]  H. Sebastian Seung,et al.  Learning the parts of objects by non-negative matrix factorization , 1999, Nature.

[217]  Alex Pothen,et al.  Graph Partitioning Algorithms with Applications to Scientific Computing , 1997 .

[218]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[219]  James C. Bezdek,et al.  Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.