title: Stability metrics for multi-source biomedical data based on simplicial projections from probability distribution distances.
abstract: Biomedical data may be composed of individuals generated from distinct, meaningful sources. Due to possible contextual biases in the processes that generate data, there may exist an undesirable and unexpected variability among the probability distribution functions (PDFs) of the source subsamples, which, when uncontrolled, may lead to inaccurate or unreproducible research results. Classical statistical methods may have difficulties to undercover such variabilities when dealing with multi-modal, multi-type, multi-variate data. This work proposes two metrics for the analysis of stability among multiple data sources, robust to the aforementioned conditions, and defined in the context of data quality assessment. Specifically, a global probabilistic deviation and a source probabilistic outlyingness metrics are proposed. The first provides a bounded degree of the global multi-source variability, designed as an estimator equivalent to the notion of normalized standard deviation of PDFs. The second provides a bounded degree of the dissimilarity of each source to a latent central distribution. The metrics are based on the projection of a simplex geometrical structure constructed from the Jensen-Shannon distances among the sources PDFs. The metrics have been evaluated and demonstrated their correct behaviour on a simulated benchmark and with real multi-source biomedical data using the UCI Heart Disease data set. The biomedical data quality assessment based on the proposed stability metrics may improve the efficiency and effectiveness of biomedical data exploitation and research.
authors.affiliation: 1 Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, 46022 València, Spain.|2 Center for Health Technology and Services Research (CINTESIS), Faculdade de Medicina da Universidade do Porto, 4200-450, Porto, Portugal.
authors.forename: Carlos
authors.initials: C
authors.lastname: Sáez
authors.affiliation: 1 Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, 46022 València, Spain.
authors.forename: Montserrat
authors.initials: M
authors.lastname: Robles
authors.affiliation: 1 Grupo de Informática Biomédica (IBIME), Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, 46022 València, Spain.|3 Grupo de Investigación Biomédica en Imagen (GIBI230), Instituto de Investigación Sanitaria (IIS), Hospital la Fe, Spain.|4 Unidad Mixta de Investigación en TICs aplicadas a la Reingeniería de Procesos Sociosanitarios (eRPSS), Instituto de Investigación Sanitaria del Hospital Universitario y Politécnico La Fe, Valencia 46026, Spain.
authors.forename: Juan M
authors.initials: JM
authors.lastname: García-Gómez
mesh_terms: D015982:Bias; D035843:Biomedical Research / Q000379:methods / Q000592:standards; D066264:Datasets as Topic / Q000592:standards*; D005260:Female; D006331:Heart Diseases; D006801:Humans; D008297:Male; D011336:Probability
keywords: data quality; data reuse; data variability; information geometry; probability distribution distances