Multimodal medical information retrieval with unsupervised rank fusion

•We propose a medical retrieval system supporting text and image queries.•It can retrieve either relevant PubMed articles or images from those articles.•It supports automatic query term expansion from the MeSH thesaurus.•Novel fusion algorithm, ISR, improves results from existing rank fusion algorit...

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Vydáno v:	Computerized medical imaging and graphics Ročník 39; s. 35 - 45
Hlavní autoři:	Mourão, André, Martins, Flávio, Magalhães, João
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Elsevier Ltd 01.01.2015
Témata:	Algorithms Artificial Intelligence Assisted query formulation Data fusion Data integration Documentation - methods Health care Information retrieval Information Storage and Retrieval - methods Internal Medicine Medical Medical search Medical Subject Headings Multimodal Imaging - methods Multimodal retrieval Natural Language Processing Other Pattern Recognition, Automated - methods PubMed Radiology Information Systems - organization & administration Retrieval Search interfaces Searching Subtraction Technique Terminology as Topic Thesauri User-Computer Interface Vocabulary, Controlled Medical search Search interfaces Data fusion Assisted query formulation Multimodal retrieval
ISSN:	0895-6111, 1879-0771, 1879-0771
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Abstract	•We propose a medical retrieval system supporting text and image queries.•It can retrieve either relevant PubMed articles or images from those articles.•It supports automatic query term expansion from the MeSH thesaurus.•Novel fusion algorithm, ISR, improves results from existing rank fusion algorithms.•We got the best result on multimodal case-based retrieval in 2013 ImageCLEFMedical Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. However, the ever-growing heterogeneous information generated in medical environments poses several challenges for retrieval systems. We propose a medical information retrieval system with support for multimodal medical case-based retrieval. The system supports medical information discovery by providing multimodal search, through a novel data fusion algorithm, and term suggestions from a medical thesaurus. Our search system compared favorably to other systems in 2013 ImageCLEFMedical.
AbstractList	Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. However, the ever-growing heterogeneous information generated in medical environments poses several challenges for retrieval systems. We propose a medical information retrieval system with support for multimodal medical case-based retrieval. The system supports medical information discovery by providing multimodal search, through a novel data fusion algorithm, and term suggestions from a medical thesaurus. Our search system compared favorably to other systems in 2013 ImageCLEFMedical. Highlights • We propose a medical retrieval system supporting text and image queries. • It can retrieve either relevant PubMed articles or images from those articles. • It supports automatic query term expansion from the MeSH thesaurus. • Novel fusion algorithm, ISR, improves results from existing rank fusion algorithms. • We got the best result on multimodal case-based retrieval in 2013 ImageCLEFMedical •We propose a medical retrieval system supporting text and image queries.•It can retrieve either relevant PubMed articles or images from those articles.•It supports automatic query term expansion from the MeSH thesaurus.•Novel fusion algorithm, ISR, improves results from existing rank fusion algorithms.•We got the best result on multimodal case-based retrieval in 2013 ImageCLEFMedical Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. However, the ever-growing heterogeneous information generated in medical environments poses several challenges for retrieval systems. We propose a medical information retrieval system with support for multimodal medical case-based retrieval. The system supports medical information discovery by providing multimodal search, through a novel data fusion algorithm, and term suggestions from a medical thesaurus. Our search system compared favorably to other systems in 2013 ImageCLEFMedical. Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. However, the ever-growing heterogeneous information generated in medical environments poses several challenges for retrieval systems. We propose a medical information retrieval system with support for multimodal medical case-based retrieval. The system supports medical information discovery by providing multimodal search, through a novel data fusion algorithm, and term suggestions from a medical thesaurus. Our search system compared favorably to other systems in 2013 ImageCLEFMedical.Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts in the diagnosis of patients and play an important role in the clinical decision process. However, the ever-growing heterogeneous information generated in medical environments poses several challenges for retrieval systems. We propose a medical information retrieval system with support for multimodal medical case-based retrieval. The system supports medical information discovery by providing multimodal search, through a novel data fusion algorithm, and term suggestions from a medical thesaurus. Our search system compared favorably to other systems in 2013 ImageCLEFMedical.
Author	Mourão, André Magalhães, João Martins, Flávio
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Cites_doi	10.1145/2071389.2071390 10.1016/j.ipm.2006.09.003 10.1007/s10278-013-9619-2 10.1016/j.ijmedinf.2003.11.024 10.1016/j.compmedimag.2008.07.006 10.1007/s00530-010-0182-0 10.1016/j.compmedimag.2010.11.008 10.1142/S0218001410007890 10.1016/j.patrec.2008.05.013 10.1016/0306-4573(94)00057-A 10.1016/j.compmedimag.2007.10.001 10.1007/s10791-005-6994-4
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Snippet	•We propose a medical retrieval system supporting text and image queries.•It can retrieve either relevant PubMed articles or images from those articles.•It... Highlights • We propose a medical retrieval system supporting text and image queries. • It can retrieve either relevant PubMed articles or images from those... Modern medical information retrieval systems are paramount to manage the insurmountable quantities of clinical data. These systems empower health care experts...
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SubjectTerms	Algorithms Artificial Intelligence Assisted query formulation Data fusion Data integration Documentation - methods Health care Information retrieval Information Storage and Retrieval - methods Internal Medicine Medical Medical search Medical Subject Headings Multimodal Imaging - methods Multimodal retrieval Natural Language Processing Other Pattern Recognition, Automated - methods PubMed Radiology Information Systems - organization & administration Retrieval Search interfaces Searching Subtraction Technique Terminology as Topic Thesauri User-Computer Interface Vocabulary, Controlled
Title	Multimodal medical information retrieval with unsupervised rank fusion
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