AIMC Topic: Metadata
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Evaluation of the prediction of CoVID-19 recovered and unrecovered cases using symptoms and patient's meta data based on support vector machine, neural network, CHAID and QUEST Models.
European review for medical and pharmacological sciences
Sep 1, 2021
OBJECTIVE: This paper aims to develop four prediction models for recovered and unrecovered cases using descriptive data of patients and symptoms of CoVID-19 patients. The developed prediction models aim to extract the important variables in predictin...
Performance Evaluation of a Deep Learning System for Differential Diagnosis of Lung Cancer With Conventional CT and FDG PET/CT Using Transfer Learning and Metadata.
Clinical nuclear medicine
Aug 1, 2021
PURPOSE: We aimed to evaluate the performance of a deep learning system for differential diagnosis of lung cancer with conventional CT and FDG PET/CT using transfer learning (TL) and metadata.
Challenges for FAIR-compliant description and comparison of crop phenotype data with standardized controlled vocabularies.
Database : the journal of biological databases and curation
May 15, 2021
Crop phenotypic data underpin many pre-breeding efforts to characterize variation within germplasm collections. Although there has been an increase in the global capacity for accumulating and comparing such data, a lack of consistency in the systemat...
Increasing metadata coverage of SRA BioSample entries using deep learning-based named entity recognition.
Database : the journal of biological databases and curation
Apr 29, 2021
High-quality metadata annotations for data hosted in large public repositories are essential for research reproducibility and for conducting fast, powerful and scalable meta-analyses. Currently, a majority of sequencing samples in the National Center...
Provenance for Biomedical Ontologies with RDF and Git.
Studies in health technology and informatics
Sep 3, 2019
The German Center for Lung Research (DZL) is a research network with the aim of researching respiratory diseases. In order to enable consortium-wide retrospective research and prospective patient recruitment, we perform data integration into a centra...
Semantic Provenance Graph for Reproducibility of Biomedical Research Studies: Generating and Analyzing Graph Structures from Published Literature.
Studies in health technology and informatics
Aug 21, 2019
OBJECTIVE: To characterize the scientific reproducibility of biomedical research studies by query and analysis of semantic provenance graphs generated from provenance metadata terms extracted from PubMed articles.
Automated Metadata Suggestion During Repository Submission.
Neuroinformatics
Jul 1, 2019
Knowledge discovery via an informatics resource is constrained by the completeness of the resource, both in terms of the amount of data it contains and in terms of the metadata that exists to describe the data. Increasing completeness in one of these...
Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
Jan 1, 2019
Phylogeography research involving virus spread and tree reconstruction relies on accurate geographic locations of infected hosts. Insufficient level of geographic information in nucleotide sequence repositories such as GenBank motivates the use of na...
SATORI: a system for ontology-guided visual exploration of biomedical data repositories.
Bioinformatics (Oxford, England)
Apr 1, 2018
MOTIVATION: The ever-increasing number of biomedical datasets provides tremendous opportunities for re-use but current data repositories provide limited means of exploration apart from text-based search. Ontological metadata annotations provide conte...
Metadata Import from RDF to i2b2.
Studies in health technology and informatics
Jan 1, 2018
Metadata management is an important task in medical informatics and highly affects the gain out of existing health information data. Data Warehouse solutions like Informatics for Integrating Biology and the Bedside (i2b2) are common tools for identif...
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