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Towards Identifying Author Confidence in Biomedical Articles

Special Issue on the Curative Power of Medical Data

Institute of Computer Science, Romanian Academy-Iasi branch, Iasi 700481, Romania
Faculty of Computer Science, Alexandru Ioan Cuza University of Iasi, Iași 700483, Romania
Cognos Business Consulting S.R.L., 7, Iuliu Maniu Blvd, Bucharest 061072, Romania
Computational Bioscience Program, University of Colorado School of Medicine, Aurora, CO 80045, USA
Department of Biostatistics, Huazhong Agricultural University, Wuhan 430070, China
Author to whom correspondence should be addressed.
Received: 12 June 2019 / Accepted: 12 June 2019 / Published: 14 June 2019
(This article belongs to the Special Issue Curative Power of Medical Data)
With the massive amounts of medical data made available online, language technologies have proven to be indispensable in processing biomedical and molecular biology literature, health data or patient records. With huge amount of reports, evaluating their impact has long ceased to be a trivial task. Linking the contents of these documents to each other, as well as to specialized ontologies, could enable access to and the discovery of structured clinical information and could foster a major leap in natural language processing and in health research. The aim of this Special Issue, “Curative Power of Medical Data” in Data, is to gather innovative approaches for the exploitation of biomedical data using semantic web technologies and linked data by developing a community involvement in biomedical research. This Special Issue contains four surveys, which include a wide range of topics, from the analysis of biomedical articles writing style, to automatically generating tests from medical references, constructing a Gold standard biomedical corpus or the visualization of biomedical data. View Full-Text
Keywords: biomedical research; medical text mining; health data analyzing biomedical research; medical text mining; health data analyzing
MDPI and ACS Style

Gîfu, D.; Trandabăț, D.; Cohen, K.; Xia, J. Special Issue on the Curative Power of Medical Data. Data 2019, 4, 85.

AMA Style

Gîfu D, Trandabăț D, Cohen K, Xia J. Special Issue on the Curative Power of Medical Data. Data. 2019; 4(2):85.

Chicago/Turabian Style

Gîfu, Daniela, Diana Trandabăț, Kevin Cohen, and Jingbo Xia. 2019. "Special Issue on the Curative Power of Medical Data" Data 4, no. 2: 85.

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