A cancer patient model based on pre-conceptual schemas: beyond encounters and cancer specificities

Authors

  • Carlos Mario Zapata Jaramillo Universidad Nacional de Colombia

DOI:

https://doi.org/10.14482/inde.43.02.365.963

Keywords:

Cancer, knowledge representation, model, patient, pre-conceptual schemas

Abstract

The first stage for solving complex problems involves their representation into a model. Some cancer patient models have been developed for representing the environment surrounding the patient and her characteristics. However, such models are far away from knowledge representations due to some reasons: generality, specificity to certain cancer types, focus on the patient/encounter, and segregated terminology/syntax. In this paper we propose a model of cancer patients in order to overcome the aforementioned problems. We select the so-called pre-conceptual schemas as the knowledge representation paradigm, because they can be instantiated for resembling details of the model and integrated with standards about medicine and cancer modeling.

References

R. Davis, H. Shrobe, P. Szolovits, “What is a knowledge representation?,” AI Magazine, no. (spring 1993), pp. 17–33, 1993. https://doi.org/10.1609/aimag.v14i1.1029

B. Kitchenham, S. Charters. Guidelines for Performing Systematic Literature Reviews in Software Engineering (version 2.3). Technical Report, Keele University and University of Durham, 2007.

D. Wittmann, C. Variamos, N. Rodriguez-Galano, L. Day, G. Grube, J. Shifferd, K. Erickson, A. Duby, T. M. Morgan, B. K. Hollenbeck, T. A. Skolarus, S. S. Salami, S. D. Kaffenberger, J. E. Montie, “Developing a patient-centered model of prostate cancer care: patient satisfaction with a survivorship program embedded in urologic-oncologic care,” Urology, vol. 160, pp. 161–167, 2022. https://doi.org/10.1016/j.urology.2021.10.046

H. Imoto, S. Yamashiro, M. Okada, “A text-based computational framework for patient-specific modeling for classification of cancers,” IScience, vol. 25, no. 3, pp. 1–18, 2022. https://doi.org/10.1016/j.isci.2022.103944

J. Meier, A. Boehm, T. Neumuth, S. Bohn, “Towards a digital patient model for head and neck tumor treatment: information integration from distributed information systems,” International Journal of Computer Assisted Radiology and Surgery, vol. 8, no. 1, pp. S219–S224, 2013. https://doi.org/10.1007/s11548-013-0870-2

R. Jayadevappa, S. Chhatre, “Patient centered care—a conceptual model and review of the state of the art,” The open health services and policy journal, vol. 4, pp. 15-25, 2011. http://dx.doi.org/10.2174/1874924001104010015

L. Berliner, H. U. Lemke, “The digital patient model and model guided therapy,” in An information technology framework for predictive, preventive and personalized medicine, first ed., Switzerland: Springer International Publishing, 2015, ch. 2, pp. 9–19. https://doi.org/10.1007/978-3-319-12166-6_2

S. A. Eschrich, J. K. Teer, P. Reisman, E. Siegel, Ch. Challa, P. Lewis, K. Fellows, E. Malpica, R. Carvajal, G. Gonzalez, S. Cukras, M. Betin-Montes, G. Aden- Buie, M. Avedon, D. Manning, A. Ch. Tan, B. L. Fridley, T. Gerke, M. Van Looveren, A. Blake, J. Greenman, D. E. Rollison, “Enabling precision medicine in cancer care through a molecular data warehouse: the Moffitt experience,” JCO clinical cancer informatics, vol. 5, pp. 561–569, 2021. https://doi.org/10.1200/CCI.20.00175

H. Yang, W. Yu, H. Zhang, F. Heng, X. Ma, N. Li, Z. Wang, X. Hou, R. Guo, Y. Lu, “Evaluation of a whole process management model based on an information system for cancer patients with pain: a prospective nonrandomized controlled study,” Asia-Pacific journal of oncology nursing, vol. 9, pp. 88–96, 2022. https://doi.org/10.1016/j.apjon.2021.12.017

N. B. Halmai, L. G. Carvajal-Carmona, “Diversifying preclinical research tools: expanding patient-derived models to address cancer health disparities,” Trends in cancer, vol. 8, no. 4, pp. 291–294, 2022. https://doi.org/10.1016/j.trecan.2022.01.007

H. U. Lemke, M. Cypko, L. Berliner, “Information integration for patient-specific modelling using MEBNs: example of laryngeal carcinoma,” International Journal of Computer Assisted Radiology and Surgery, vol. 8, no. 1, pp. S239–S248, 2012.

Board on Health Care Services, Delivering high-quality cancer care: charting a new course for a system in crisis. Washington D.C.: The National Academies Press, 2013. https://doi.org/10.17226/18359

H. Hassankhani, A. Rahmani, F. Taleghani, Z. Sanaat, J. Dehghannezhad, “Palliative care models for cancer patients: learning for planning in nursing (review),” Journal of cancer education, vol. 35, pp. 3–13, 2020. https://doi.org/10.1007/s13187-019-01532-3

P. Tralongo, F. Ferraú, N. Borsellino, F. VErderame, M. Caruso, D. Giuffrida, A. Butera, V. Gebbia, “Cancer patient-centered home care: a new model for health care in oncology,” Therapeutics and clinical risk management, vol. 7, pp. 387–392, 2011. https://doi.org/10.2147/TCRM.S22119

C. M. Zapata-Jaramillo, A. Gelbukh, F. Arango, “Pre-conceptual schemas: a conceptual-graph-like knowledge representation for requirements elicitation,” Lecture notes in computer science, vol. 4293, pp. 27–37, 2006. https://doi.org/10.1007/11925231_3

C. M. Zapata-Jaramillo, G. L. Giraldo, S. Londoño, “Esquemas preconceptuales ejecutables,” Revista avances en sistemas e informática, vol. 8, no. 1, pp. 15–23, 2010.

G. Anderson. Fundamentals of educational research. London, The Falmer Press: London, 1990.

Published

2025-07-01

How to Cite

[1]
C. M. Zapata Jaramillo, “A cancer patient model based on pre-conceptual schemas: beyond encounters and cancer specificities”, Ing. y Des., vol. 43, no. 2, pp. 177–199, Jul. 2025.