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Pattern recognition in data as a diagnosis tool

التفاصيل البيبلوغرافية
العنوان: Pattern recognition in data as a diagnosis tool
المؤلفون: Ana Carpio, Alejandro Simón, Alicia Torres, Luis F. Villa
المصدر: Journal of Mathematics in Industry, Vol 12, Iss 1, Pp 1-24 (2022)
بيانات النشر: SpringerOpen, 2022.
سنة النشر: 2022
المجموعة: LCC:Mathematics
LCC:Industry
مصطلحات موضوعية: Pattern classification, Hyperparameter selection, Plackett-Luce models, Hamming distance, Dynamic time warping distance, Wasserstein distance, Mathematics, QA1-939, Industry, HD2321-4730.9
الوصف: Abstract Medical data often appear in the form of numerical matrices or sequences. We develop mathematical tools for automatic screening of such data in two medical contexts: diagnosis of systemic lupus erythematosus (SLE) patients and identification of cardiac abnormalities. The idea is first to implement adequate data normalizations and then identify suitable hyperparameters and distances to classify relevant patterns. To this purpose, we discuss the applicability of Plackett-Luce models for rankings to hyperparameter and distance selection. Our tests suggest that, while Hamming distances seem to be well adapted to the study of patterns in matrices representing data from laboratory tests, dynamic time warping distances provide robust tools for the study of cardiac signals. The techniques developed here may set a basis for automatic screening of medical information based on pattern comparison.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2190-5983
Relation: https://doaj.org/toc/2190-5983
DOI: 10.1186/s13362-022-00119-w
URL الوصول: https://doaj.org/article/1906260a28454239b4effd5689122680
رقم الأكسشن: edsdoj.1906260a28454239b4effd5689122680
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:21905983
DOI:10.1186/s13362-022-00119-w