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SwellShark [118] is a framework for biomedical NER that requires no human-labeled data but does make use of resources for weak supervision (e.g., UMLS semantic types). The SparkText framework [119] uses Apache Spark data streaming, a NoSQL database, and basic machine learning methods to build predictive models from scientific articles.
EMBnet.journal; Evolutionary Bioinformatics; GigaScience; IEEE/ACM Transactions on Computational Biology and Bioinformatics; Journal of the American Medical Informatics Association; Journal of Bioinformatics and Computational Biology; Journal of Biomedical Informatics; Journal of Computational Biology; Journal of Mathematical Biology; Journal ...
Machine learning in bioinformatics is the application of machine learning algorithms to bioinformatics, [1] including genomics, proteomics, microarrays, systems biology, evolution, and text mining. [ 2 ] [ 3 ]
Full-text aggregator of open access journals and papers (>17,000 journals) from all academic disciplines. Free No [9] Paperity Sp. z o.o. Semantic Scholar: Multidisciplinary: 8,100,000 [10] (200,000,000 metadata [11]) Mostly computer science and biomedical publications. Powered by semantic analysis. Free Semi-free [10] Allen Institute for ...
High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce ...
The journal was established by Homer R. Warner in 1967 under the name Computers and Biomedical Research and was renamed beginning with Volume 34 in 2001, when it was redesigned under the leadership of Edward H. Shortliffe as its editor-in-chief. The current editor-in-chief is Mor Peleg.
Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics, Biomedical informatics, and machine learning, with the goal of understanding biological and medical data.
BioData Mining is a peer-reviewed open access scientific journal covering data mining methods applied to computational biology and medicine established in 2008. It is published by BioMed Central and the editors-in-chief are Jason H. Moore and Marylyn D. Ritchie ( University of Pennsylvania ).