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Differential diagnostic reasoning method for benign paroxysmal positional vertigo based on dynamic uncertain causality graph. (English) Zbl 1431.92052
Summary: The accurate differentiation of the subtypes of benign paroxysmal positional vertigo (BPPV) can significantly improve the efficacy of repositioning maneuver in its treatment and thus reduce unnecessary clinical tests and inappropriate medications. In this study, attempts have been made towards developing approaches of causality modeling and diagnostic reasoning about the uncertainties that can arise from medical information. A dynamic uncertain causality graph-based differential diagnosis model for BPPV including 354 variables and 885 causality arcs is constructed. New algorithms are also proposed for differential diagnosis through logical and probabilistic inference, with an emphasis on solving the problems of intricate and confounding disease factors, incomplete clinical observations, and insufficient sample data. This study further uses vertigo cases to test the performance of the proposed method in clinical practice. The results point to high accuracy, a satisfactory discriminatory ability for BPPV, and favorable robustness regarding incomplete medical information. The underlying pathological mechanisms and causality semantics are verified using compact graphical representation and reasoning process, which enhance the interpretability of the diagnosis conclusions.
92C50 Medical applications (general)
05C90 Applications of graph theory
Full Text: DOI
[1] Bhattacharyya, N.; Baugh, R. F.; Orvidas, L., Clinical practice guideline: benign paroxysmal positional vertigo, Otolaryngology—Head and Neck Surgery, 139, 5_suppl, S47-S81 (2008)
[2] Oghalai, J. S.; Manolidis, S.; Barth, J. L.; Stewart, M. G.; Jenkins, H. A., Unrecognized benign paroxysmal positional vertigo in elderly patients, Otolaryngology—Head and Neck Surgery, 122, 5, 630-634 (2000)
[3] Prim-Espada, M. P.; De Diego-Sastre, J. I.; Pérez-Fernández, E., Estudio metaanalítico de la eficacia de la maniobra de Epley en el vértigo posicional paroxístico benigno, Neurología, 25, 5, 295-299 (2010)
[4] Parnes, L. S.; Agrawal, S. K.; Atlas, J., Diagnosis and management of benign paroxysmal positional vertigo (BPPV), Canadian Medical Association Journal, 169, 7, 681-693 (2003)
[5] Li, J. C.; Epley, J., The 360-degree maneuver for treatment of benign positional vertigo, Otology & Neurotology, 27, 1, 71-77 (2006)
[6] Isola, R.; Carvalho, R.; Tripathy, A. K., Knowledge discovery in medical systems using differential diagnosis, LAMSTAR, and \(k\)-NN, IEEE Transactions on Information Technology in Biomedicine, 16, 6, 1287-1295 (2012)
[7] Barabasi, A. L.; Gulbahce, N.; Loscalzo, J., Network medicine: a network-based approach to human disease, Nature Reviews Genetics, 12, 1, 56-68 (2011)
[8] Mira, E.; Buizza, A.; Magenes, G.; Manfrin, M.; Schmid, R., Expert systems as a diagnostic aid in otoneurology, Journal for Oto-Rhino-Laryngology and Its Related Specialties (ORL), 52, 2, 96-103 (1990)
[9] Gavilán, C. É. S.; Gallego, J. É.; Gavilán, J., Carnisel: an expert system for vestibular diagnosis, Acta Oto-Laryngologica, 110, 3-4, 161-167 (1990)
[10] Kentala, E.; Pyykko, I.; Auramo, Y.; Laurikkala, J.; Juhola, M., Otoneurological expert system for vertigo, Acta Oto-Laryngologica, 119, 5, 517-521 (1999)
[11] Kentala, E.; Viikki, K.; Pyykko, I.; Juhola, M., Production of diagnostic rules from a neurotologic database with decision trees, Annals of Otology, Rhinology and Laryngology, 109, 2, 170-176 (2000)
[12] Song, J. W.; Lee, J. H.; Choi, J. H.; Chun, S. J., Automatic differential diagnosis of pancreatic serous and mucinous cystadenomas based on morphological features, Computers in Biology and Medicine, 43, 1, 1-15 (2013)
[13] Lopes, M. H.; Ortega, N. R.; Silveira, P. S.; Massad, E.; Higa, R.; Marin Hde, F., Fuzzy cognitive map in differential diagnosis of alterations in urinary elimination: a nursing approach, International Journal of Medical Informatics, 82, 3, 201-208 (2013)
[14] Salvatore, C.; Cerasa, A.; Castiglioni, I., Machine learning on brain MRI data for differential diagnosis of Parkinson’s disease and Progressive Supranuclear Palsy, Journal of Neuroscience Methods, 222, 230-237 (2014)
[15] Mudali, D.; Teune, L. K.; Renken, R. J.; Leenders, K. L.; Roerdink, J. B., Classification of Parkinsonian syndromes from FDG-PET brain data using decision trees with SSM/PCA features, Computational and Mathematical Methods in Medicine, 2015 (2015)
[16] Ota, M.; Nakata, Y.; Ito, K., Differential diagnosis tool for parkinsonian syndrome using multiple structural brain measures, Computational and Mathematical Methods in Medicine, 2013 (2013)
[17] Prashanth, R.; Dutta Roy, S.; Mandal, P. K.; Ghosh, S., Automatic classification and prediction models for early Parkinson’s disease diagnosis from SPECT imaging, Expert Systems with Applications, 41, 7, 3333-3342 (2014)
[18] Ceccon, S.; Garway-Heath, D. F.; Crabb, D. P.; Tucker, A., Exploring early glaucoma and the visual field test: classification and clustering using Bayesian networks, IEEE Journal of Biomedical and Health Informatics, 18, 3, 1008-1014 (2013)
[19] Rodriguez, J. D.; Perez, A.; Arteta, D.; Tejedor, D.; Lozano, J. A., Using multidimensional bayesian network classifiers to assist the treatment of multiple sclerosis, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 42, 6, 1705-1715 (2012)
[20] He, L.; Hu, D.; Wan, M.; Wen, Y.; Von Deneen, K. M.; Zhou, M., Common bayesian network for classification of EEG-based multiclass motor imagery BCI, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46, 6, 843-854 (2016)
[21] Oliva, J.; Serrano, J. I.; del Castillo, M. D.; Iglesias, Á., A methodology for the characterization and diagnosis of cognitive impairments—application to specific language impairment, Artificial Intelligence in Medicine, 61, 89-96 (2014)
[22] Melin, P.; Amezcua, J.; Valdez, F.; Castillo, O., A new neural network model based on the LVQ algorithm for multi-class classification of arrhythmias, Information Sciences, 279, 483-497 (2014)
[23] Fisher, A. C.; Lake, S. P.; Cunningham, I. P.; Chandna, A., Web-StrabNet: a web-based expert system for the differential diagnosis of vertical strabismus (squint), Computational and Mathematical Methods in Medicine, 11, 1, 89-97 (2010) · Zbl 1202.92038
[24] Nahar, J.; Imam, T.; Tickle, K. S.; Chen, Y.-P. P., Computational intelligence for heart disease diagnosis: a medical knowledge driven approach, Expert Systems with Applications, 40, 1, 96-104 (2013)
[25] Yue, K.; Fang, Q.; Wang, X.; Li, J.; Liu, W., A parallel and incremental approach for data-intensive learning of bayesian networks, IEEE Transactions on Cybernetics, 45, 12, 2890-2904 (2015)
[26] Cano, A.; Masegosa, A. R.; Moral, S., A method for integrating expert knowledge when learning bayesian networks from data, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 41, 5, 1382-1394 (2011)
[27] Guessoum, S.; Laskri, M. T.; Lieber, J., RespiDiag: a case-based reasoning system for the diagnosis of chronic obstructive pulmonary disease, Expert Systems with Applications, 41, 2, 267-273 (2014)
[28] Zhang, Q.; Dong, C. L.; Cui, Y.; Yang, Z. H., Dynamic Uncertain Causality Graph for knowledge representation and probabilistic reasoning: statistics base, matrix, and application, IEEE Transactions on Neural Networks and Learning Systems, 25, 4, 645-663 (2014)
[29] Zhang, Q., Dynamic Uncertain Causality Graph for knowledge representation and probabilistic reasoning: directed cyclic graph and joint probability distribution, IEEE Transactions on Neural Networks and Learning Systems, 26, 7, 1503-1517 (2015)
[30] Dong, C.; Wang, Y.; Zhang, Q.; Wang, N., The methodology of Dynamic Uncertain Causality Graph for intelligent diagnosis of vertigo, Computer Methods and Programs in Biomedicine, 113, 1, 162-174 (2014)
[31] Dong, C.; Zhou, Z.; Zhang, Q., Cubic dynamic uncertain causality graph: a new methodology for modeling and reasoning about complex faults with negative feedbacks, IEEE Transactions on Reliability, 67, 3, 920-932 (2018)
[32] Fife, T. D., Benign paroxysmal positional vertigo, Seminars In Neurology, 29, 5, 500-508 (2009)
[33] Korres, S. G.; Balatsouras, D. G.; Papouliakos, S.; Ferekidis, E., Benign paroxysmal positional vertigo and its management, Medical Science Monitor, 13, 6, CR275-82 (2007)
[34] Balatsouras, D. G.; Korres, S. G., Subjective benign paroxysmal positional vertigo, Otolaryngology—Head and Neck Surgery, 146, 1, 98-103 (2012)
[35] Choi, S. J.; Lee, J. B.; Lim, H. J., Clinical features of recurrent or persistent benign paroxysmal positional vertigo, Otolaryngology—Head and Neck Surgery, 147, 919-924 (2012)
[36] von Brevern, M.; Bertholon, P.; Brandt, T., Benign paroxysmal positional vertigo: diagnostic criteria, Journal of Vestibular Research, 25, 3-4, 105-117 (2015)
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