Publication: Técnicas matemáticas para diagnosis médica
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2021-02-24
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Abstract
El campo de las matemáticas para ciencias de la salud hace referencia a los métodos y herramientas matemáticas que se aplican en la solución de problemas que pertenecen al área de las ciencias de la salud y de la medicina. Se trata de un campo muy amplio y el presente Trabajo de Fin de Grado centra la atención en el riesgo que presenta un individuo de sufrir una fractura. Se estudia y testea el algoritmo de la herramienta Fracture Risk Assesment Tool (FRAX) en una base de datos sintética. Esta aplicación calcula la probabilidad a 10 años que presenta un individuo entre 40 y 90 años de sufrir fractura de cadera o cualquier otra fractura osteoporótica a partir de una serie de factores clínicos de riesgo. Con la intención de mejorar la precisión del algoritmo, se añade a la información inicial un factor de riesgo específico: una serie de radiografías del paciente. Se realiza una comparación entre las imágenes con rayos X de manera automatizada. Así, la probabilidad de fractura puede aumentar con el empeoramiento de un hueso en concreto o de manera análoga podría disminuir con la mejora de ese hueso.
The field of mathematics for health sciences refers to the mathematical methods that are applied in the solution of problems that belong to the area of health sciences and medicine. It is a very broad field, and this Final Degree Project focuses on the risk of an individual suffering a fracture. The algorithm of the Fracture Risk Assessment Tool (FRAX) is studied and tested on a synthetic database. This application calculates the 10-year probability of an individual between 40 and 90 years of suffering a hip fracture or any other osteoportic fracture based on a series of clinical risk factors. In order to improve the accuracy of the algorithm, a specific risk factor is added to the initial information: a series of radiographs of the patient. A comparison between the X-ray images is performed in an automated way. Thus, the probability of fracture may increase with the worsening of a particular bone, or similarly it may decrease with the improvement of that bone.
The field of mathematics for health sciences refers to the mathematical methods that are applied in the solution of problems that belong to the area of health sciences and medicine. It is a very broad field, and this Final Degree Project focuses on the risk of an individual suffering a fracture. The algorithm of the Fracture Risk Assessment Tool (FRAX) is studied and tested on a synthetic database. This application calculates the 10-year probability of an individual between 40 and 90 years of suffering a hip fracture or any other osteoportic fracture based on a series of clinical risk factors. In order to improve the accuracy of the algorithm, a specific risk factor is added to the initial information: a series of radiographs of the patient. A comparison between the X-ray images is performed in an automated way. Thus, the probability of fracture may increase with the worsening of a particular bone, or similarly it may decrease with the improvement of that bone.
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[1] B. L. Riggs and L. J. Melton, “The worldwide problem of osteoporosis: Insights afforded by epidemiology,” Bone, vol. 17, no. 5 SUPPL. 1, 1995, doi: 10.1016/8756-3282(95)00258-4.
[2] J. A. Kanis and J. A. Kanis, “Assessment of fracture risk and its application to screening for postmenopausal osteoporosis: Synopsis of a WHO report,” Osteoporos. Int., vol. 4, no. 6, pp. 368–381, Nov. 1994, doi: 10.1007/BF01622200.
[3] J. A. Kanis, O. Johnell, A. Oden, H. Johansson, and E. McCloskey, “FRAXTM and the assessment of fracture probability in men and women from the UK,” Osteoporos. Int., vol. 19, no. 4, pp. 385–397, Apr. 2008, doi: 10.1007/s00198-007-0543-5.
[4] C. De Laet, A. Odén, H. Johansson, O. Johnell, B. Jönsson, and J. A. Kanis, “The impact of the use of multiple risk indicators for fracture on case-finding strategies: A mathematical approach,” Osteoporos. Int., vol. 16, no. 3, pp. 313–318, 2005, doi: 10.1007/s00198-004-1689-z.
[5] S. R. Cummings et al., “Risk Factors for Hip Fracture in White Women,” N. Engl. J. Med., vol. 332, no. 12, pp. 767–773, Mar. 1995, doi: 10.1056/nejm199503233321202.
[6] J. A. Kanis et al., “A meta-analysis of prior corticosteroid use and fracture risk,” J. Bone Miner. Res., vol. 19, no. 6, pp. 893–899, 2004, doi: 10.1359/JBMR.040134.
[7] O. A, D. A, D. W, J. O, J. B, and K. JA, “Lifetime risk of hip fractures is underestimated,” Osteoporos. Int., vol. 8, no. 6, 1998, doi: 10.1007/S001980050105.
[8] C. I. Sánchez Montero, “Osteoporosis y diagnóstico por radiografía convencional de fracturas vertebrales osteoporóticas,” Rev. Medica Sinerg., vol. 3, no. 10, pp. 7–11, Sep. 2018, doi: 10.31434/rms.v3i10.143.
[9] Y. Rubner, C. Tomasi, and L. J. Guibas, “Earth mover’s distance as a metric for image retrieval,” Int. J. Comput. Vis., vol. 40, no. 2, pp. 99–121, Nov. 2000, doi: 10.1023/A:1026543900054.