@inbook{
 type = {inbook},
 year = {2018},
 keywords = {Data fusion,Diagnostic decision support,Multimodal fusion,Physiological signal,Signal processing},
 pages = {1-15},
 websites = {http://link.springer.com/10.1007/978-3-319-98998-3_1},
 id = {32a0a39c-b8a6-3443-9385-2b39d1db654b},
 created = {2021-05-10T23:31:46.538Z},
 file_attached = {false},
 profile_id = {aba9653c-d139-3f95-aad8-969c487ed2f3},
 group_id = {b8c873a2-ed58-396e-b124-8a273665874f},
 last_modified = {2021-05-10T23:31:46.538Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Uribe2018},
 private_publication = {false},
 abstract = {The analysis of physiological signals is widely used for the development of diagnosis support tools in medicine, and it is currently an open research field. The use of multiple signals or physiological measures as a whole has been carried out using data fusion techniques commonly known as multimodal fusion, which has demonstrated its ability to improve the accuracy of diagnostic care systems. This paper presents a review of state of the art, putting in relief the main techniques, challenges, gaps, advantages, disadvantages, and practical considerations of data fusion applied to the analysis of physiological signals oriented to diagnosis decision support. Also, physiological signals data fusion architecture oriented to diagnosis is proposed.},
 bibtype = {inbook},
 author = {Uribe, Y. F. and Alvarez-Uribe, K. C. and Peluffo-Ordoñez, D. H. and Becerra, M. A.},
 doi = {10.1007/978-3-319-98998-3_1},
 chapter = {Physiological Signals Fusion Oriented to Diagnosis - A Review},
 title = {Communications in Computer and Information Science}
}

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