Editorial Special Issues

Advances in computational methods for process and data mining in healthcare

  • Received: 18 June 2024 Revised: 04 July 2024 Accepted: 07 July 2024 Published: 10 July 2024
  • Citation: Marco Pegoraro, Elisabetta Benevento, Davide Aloini, Wil M.P. van der Aalst. Advances in computational methods for process and data mining in healthcare[J]. Mathematical Biosciences and Engineering, 2024, 21(7): 6603-6607. doi: 10.3934/mbe.2024288

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    [2] E. Rojas, J. Munoz-Gama, M. Sepúlveda, D. Capurro, Process mining in healthcare: A literature review, J. Biomed. Inform., 61 (2016), 224–236. https://doi.org/10.1016/j.jbi.2016.04.007 doi: 10.1016/j.jbi.2016.04.007
    [3] M. Ghasemi, D. Amyot, Process mining in healthcare: A systematised literature review, Int. J. Electron. Healthcare, 9 (2016), 60–88. https://doi.org/10.1504/IJEH.2016.078745 doi: 10.1504/IJEH.2016.078745
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    [7] E. De Roock, N. Martin, Process mining in healthcare - An updated perspective on the state of the art, J. Biomed. Inform., 127 (2022), 103995. https://doi.org/10.1016/j.jbi.2022.103995 doi: 10.1016/j.jbi.2022.103995
    [8] W. M. P. van der Aalst, A. Adriansyah, A. K. A. De Medeiros, F. Arcieri, T. Baier, T. Blickle, et al., Process mining manifesto, in Business Process Management Workshops: BPM 2011 International Workshops, Clermont-Ferrand, France, August 29, 2011, Revised Selected Papers, Part I (eds. F. Daniel, K. Barkaoui, S. Dustdar), 9 (2012), 169–194. https://doi.org/10.1007/978-3-642-28108-2_19
    [9] R. S. Mans, W. M. P. van der Aalst, R. J. B. Vanwersch, Process mining in healthcare: Evaluating and exploiting operational healthcare processes, Springer International Publishing, (2015). https://doi.org/10.1007/978-3-319-16071-9
    [10] F. Daniel, Q. Z. Sheng, H. Motahari, Business process management workshops - BPM 2018 international workshops, Sydney, NSW, Australia, September 9-14, 2018, revised papers, Lecture Notes in Business Information Processing, 342 (2019). https://doi.org/10.1007/978-3-030-11641-5 doi: 10.1007/978-3-030-11641-5
    [11] J. Munoz-Gama, N. Martin, C. Fernandez-Llatas, O. Johnson, M. Sepúlveda, Innovative informatics methods for process mining in health care, J. Biomed. Inform., 134 (2022), 104203. https://doi.org/10.1016/j.jbi.2022.104203 doi: 10.1016/j.jbi.2022.104203
    [12] J. Munoz-Gama, N. Martin, C. Fernandez-Llatas, O. A. Johnson, M. Sepúlveda, E. Helm, et al., Process mining for healthcare: Characteristics and challenges, J. Biomed. Inform., 127 (2022), 103994. https://doi.org/10.1016/j.jbi.2022.103994 doi: 10.1016/j.jbi.2022.103994
    [13] N. Martin, N. Wittig, J. Munoz-Gama, Using Process Mining in Healthcare, in Process Mining Handbook (eds. W. M. P. van der Aalst, J. Carmona), Lecture Notes in Business Information Processing, 448 (2022), 416–444, Springer. https://doi.org/10.1007/978-3-031-08848-3_14
    [14] M. Jiang, B. Zhou, L. Chen, Identification of drug side effects with a path-based method, Math. Biosci. Eng., 19 (2022), 5754–5771. https://doi.org/10.3934/mbe.2022269 doi: 10.3934/mbe.2022269
    [15] M. N. Tiftik, T. G. Erdogan, A. K. Tarhan, A framework for multi-perspective process mining into a BPMN process model, Math. Biosci. Eng., 19 (2022), 11800–11820. https://doi.org/10.3934/mbe.2022550 doi: 10.3934/mbe.2022550
    [16] J. Grüger, M. Kuhn, R. Bergmann, Reconstructing invisible deviating events: A conformance checking approach for recurring events, Math. Biosci. Eng., 19 (2022), 11782–11799. https://doi.org/10.3934/mbe.2022549 doi: 10.3934/mbe.2022549
    [17] Y. Shi, X. Huang, Z. Du, J. Tan, Analysis of single-cell RNA-sequencing data identifies a hypoxic tumor subpopulation associated with poor prognosis in triple-negative breast cancer, Math. Biosci. Eng., 19 (2022), 5793–5812. https://doi.org/10.3934/mbe.2022271 doi: 10.3934/mbe.2022271
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