A Hybrid Clustering Approach for Diagnosing Medical Diseases

被引：10
|
作者：
Simic, Svetlana [1 ]
Bankovic, Zorana [2 ]
Simic, Dragan [3 ]
Simic, Svetislav D. [3 ]
机构：
[1] Univ Novi Sad, Fac Med, Hajduk Veljkova 1-9, Novi Sad 21000, Serbia
[2] Frontiers Media SA, Pozuelo Alarcon Sn, Madrid, Spain
[3] Univ Novi Sad, Fac Tech Sci, Trg Dositeja Obradovica 6, Novi Sad 21000, Serbia
来源：
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS (HAIS 2018) | 2018年 / 10870卷
关键词：
Data clustering; Maximum likelihood estimates clustering; Number of clusters; Fuzzy partition method;
D O I：
10.1007/978-3-319-92639-1_62
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Clustering is one of the most fundamental and essential data analysis tasks with broad applications. It has been studied extensively in various research fields, including data mining, machine learning, pattern recognition, and in scientific, engineering, social, economic, and biomedical data analysis. This paper is focused on a new strategy based on a hybrid model for combining fuzzy partition method and maximum likelihood estimates clustering algorithm for diagnosing medical diseases. The proposed hybrid system is first tested on well-known Iris data set and then on three data sets for diagnosing medical diseases from UCI data repository.
引用
收藏
页码：741 / 752
页数：12
相关论文
共 50 条
  • [41] A novel agglomerative hierarchical approach for clustering in medical databases
    1600, Springer Verlag (235):
  • [42] Clustering-based approach for medical data classification
    Kodabagi, Mallikarjun M.
    Tikotikar, Ahelam
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2019, 31 (14):
  • [43] Clustering web access patterns based on hybrid approach
    Wu, Rui
    FIFTH INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, VOL 1, PROCEEDINGS, 2008, : 52 - 56
  • [44] A Hybrid Metaheuristic Approach for Automatic Clustering of Breast Cancer
    Badr, Yasmin A.
    Abou El-Naga, Amany H.
    5TH INTERNATIONAL CONFERENCE ON COMPUTING AND INFORMATICS (ICCI 2022), 2022, : 392 - 399
  • [45] A hybrid optimization approach based on clustering and chaotic sequences
    Galvez, Jorge
    Cuevas, Erik
    Becerra, Hector
    Avalos, Omar
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2020, 11 (02) : 359 - 401
  • [46] Evaluation of a Hybrid Clustering Approach for a Benchmark Industrial System
    Fontes, Cristiano Hora
    Budman, Hector
    INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2018, 57 (32) : 11039 - 11049
  • [47] A Hybrid Fuzzy Clustering Approach for Fertile and Unfertile Analysis
    Soltanzadeh, Shima
    Zarandi, Mohammad Hosein Fazel
    Astanjin, Mojtaba Barzegar
    2016 ANNUAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY (NAFIPS), 2016,
  • [48] A Hybrid approach to improving clustering accuracy using SVM
    Shah, Zubair
    Mahmood, Abdun Naser
    Mustafa, Abdul K.
    PROCEEDINGS OF THE 2013 IEEE 8TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2013, : 783 - 788
  • [49] An Hybrid Data Stream Summarizing Approach by Sampling and Clustering
    Gabsi, Nesrine
    Clerot, Fabrice
    Hebrail, Georges
    ADVANCES IN KNOWLEDGE DISCOVERY AND MANAGEMENT, 2010, 292 : 181 - +
  • [50] A hybrid optimization approach based on clustering and chaotic sequences
    Jorge Gálvez
    Erik Cuevas
    Héctor Becerra
    Omar Avalos
    International Journal of Machine Learning and Cybernetics, 2020, 11 : 359 - 401
12345