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Logical analysis of data—An overview: From combinatorial optimization to medical applications

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  • Peter Hammer
  • Tibérius Bonates

Abstract

The paper presents a review of the basic concepts of the Logical Analysis of Data (LAD), along with a series of discrete optimization models associated to the implementation of various components of its general methodology, as well as an outline of applications of LAD to medical problems. The combinatorial optimization models described in the paper represent variations on the general theme of set covering, including some with nonlinear objective functions. The medical applications described include the development of diagnostic and prognostic systems in cancer research and pulmonology, risk assessment among cardiac patients, and the design of biomaterials. Copyright Springer Science + Business Media, LLC 2006

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  • Peter Hammer & Tibérius Bonates, 2006. "Logical analysis of data—An overview: From combinatorial optimization to medical applications," Annals of Operations Research, Springer, vol. 148(1), pages 203-225, November.
    • Handle: RePEc:spr:annopr:v:148:y:2006:i:1:p:203-225:10.1007/s10479-006-0075-y
    DOI: 10.1007/s10479-006-0075-y
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    References listed on IDEAS

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    1. Hammer, P.L. & Kogan, A. & Lejeune, M.A., 2006. "Modeling country risk ratings using partial orders," European Journal of Operational Research, Elsevier, vol. 175(2), pages 836-859, December.
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    Cited by:

    1. Ya-Ju Fan & Wanpracha Chaovalitwongse, 2010. "Optimizing feature selection to improve medical diagnosis," Annals of Operations Research, Springer, vol. 174(1), pages 169-183, February.
    2. Endre Boros & Yves Crama & Peter Hammer & Toshihide Ibaraki & Alexander Kogan & Kazuhisa Makino, 2011. "Logical analysis of data: classification with justification," Annals of Operations Research, Springer, vol. 188(1), pages 33-61, August.
    3. Lejeune, Miguel & Lozin, Vadim & Lozina, Irina & Ragab, Ahmed & Yacout, Soumaya, 2019. "Recent advances in the theory and practice of Logical Analysis of Data," European Journal of Operational Research, Elsevier, vol. 275(1), pages 1-15.
    4. Miguel A. Lejeune, 2012. "Pattern-Based Modeling and Solution of Probabilistically Constrained Optimization Problems," Operations Research, INFORMS, vol. 60(6), pages 1356-1372, December.
    5. Pierre Hansen & Christophe Meyer, 2011. "A new column generation algorithm for Logical Analysis of Data," Annals of Operations Research, Springer, vol. 188(1), pages 215-249, August.
    6. Caserta, Marco & Reiners, Torsten, 2016. "A pool-based pattern generation algorithm for logical analysis of data with automatic fine-tuning," European Journal of Operational Research, Elsevier, vol. 248(2), pages 593-606.
    7. Elnaz Gholipour & B'ela Vizv'ari & Zolt'an Lakner, 2020. "Reconstruction Rating Model of Sovereign Debt by Logical Analysis of Data," Papers 2011.14112, arXiv.org.
    8. de Vos, Wout & Balvert, Marleen, 2023. "RPA : Learning Interpretable Input-Output Relationships by Counting Samples," Other publications TiSEM 70276b7f-9026-46ad-a8e8-1, Tilburg University, School of Economics and Management.
    9. Maurizio Boccia & Antonio Sforza & Claudio Sterle, 2020. "Simple Pattern Minimality Problems: Integer Linear Programming Formulations and Covering-Based Heuristic Solving Approaches," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 1049-1060, October.
    10. Pierre Lemaire, 2011. "Extensions of Logical Analysis of Data for growth hormone deficiency diagnoses," Annals of Operations Research, Springer, vol. 186(1), pages 199-211, June.
    11. Bagchi, Prabir & Lejeune, Miguel A. & Alam, A., 2014. "How supply competency affects FDI decisions: Some insights," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 239-251.
    12. Miguel Lejeune, 2012. "Pattern definition of the p-efficiency concept," Annals of Operations Research, Springer, vol. 200(1), pages 23-36, November.
    13. Travaughn C. Bain & Juan F. Avila-Herrera & Ersoy Subasi & Munevver Mine Subasi, 2020. "Logical analysis of multiclass data with relaxed patterns," Annals of Operations Research, Springer, vol. 287(1), pages 11-35, April.
    14. Ahmed Ragab & Mohamed-Salah Ouali & Soumaya Yacout & Hany Osman, 2016. "Remaining useful life prediction using prognostic methodology based on logical analysis of data and Kaplan–Meier estimation," Journal of Intelligent Manufacturing, Springer, vol. 27(5), pages 943-958, October.
    15. Maurizio Maravalle & Federica Ricca & Bruno Simeone & Vincenzo Spinelli, 2015. "Carpal Tunnel Syndrome automatic classification: electromyography vs. ultrasound imaging," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 100-123, April.
    16. Fawaz Alsolami & Talha Amin & Igor Chikalov & Mikhail Moshkov, 2018. "Bi-criteria optimization problems for decision rules," Annals of Operations Research, Springer, vol. 271(2), pages 279-295, December.
    17. de Vos, Wout & Balvert, Marleen, 2023. "RPA : Learning Interpretable Input-Output Relationships by Counting Samples," Discussion Paper 2023-015, Tilburg University, Center for Economic Research.
    18. Yasser Shaban & Mouhab Meshreki & Soumaya Yacout & Marek Balazinski & Helmi Attia, 2017. "Process control based on pattern recognition for routing carbon fiber reinforced polymer," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 165-179, January.
    19. Dursun Delen & Madhav Erraguntla & Richard Mayer & Chang-Nien Wu, 2011. "Better management of blood supply-chain with GIS-based analytics," Annals of Operations Research, Springer, vol. 185(1), pages 181-193, May.
    20. Jocelyn, Sabrina & Chinniah, Yuvin & Ouali, Mohamed-Salah & Yacout, Soumaya, 2017. "Application of logical analysis of data to machinery-related accident prevention based on scarce data," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 223-236.
    21. Miguel Lejeune & François Margot, 2011. "Optimization for simulation: LAD accelerator," Annals of Operations Research, Springer, vol. 188(1), pages 285-305, August.

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