Scientific Publications

@article{nokey,

title = {Using Machine Learning to Collect and Facilitate Remote Access to Biomedical Databases: Development of the Biomedical Database Inventory},

author = {E Rosado and M Garcia-Remesal and S Paraiso-Medina and A Pazos and V Maojo},

editor = {JMIR Publications Inc., Toronto, Canada},

url = {https://medinform.jmir.org/2021/2/e22976/},

doi = {10.2196/22976 },

issn = {2291-9694},

year  = {2021},

date = {2021-02-25},

journal = {JMIR Medical Informatics},

volume = {9},

number = {2},

abstract = {Background: Currently, existing biomedical literature repositories do not commonly provide users with specific means to locate and remotely access biomedical databases. Objective: To address this issue, we developed the Biomedical Database Inventory (BiDI), a repository linking to biomedical databases automatically extracted from the scientific literature. BiDI provides an index of data resources and a path to access them seamlessly. Methods: We designed an ensemble of deep learning methods to extract database mentions. To train the system, we annotated a set of 1242 articles that included mentions of database publications. Such a data set was used along with transfer learning techniques to train an ensemble of deep learning natural language processing models targeted at database publication detection. Results: The system obtained an F1 score of 0.929 on database detection, showing high precision and recall values. When applying this model to the PubMed and PubMed Central databases, we identified over 10,000 unique databases. The ensemble model also extracted the weblinks to the reported databases and discarded irrelevant links. For the extraction of weblinks, the model achieved a cross-validated F1 score of 0.908. We show two use cases: one  related to ``omics'' and the other related to the COVID-19 pandemic. Conclusions: BiDI enables access to biomedical resources over the internet and facilitates data-driven research and other scientific initiatives. The repository is openly available online and will be regularly updated with an automatic text processing pipeline. The approach can be reused to create repositories of different types (ie, biomedical and others). },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32308839,

title = {genoĐraw: A Web Ŧool for Đeveloping Pedigree Điagrams Using the Standardized Ħuman Pedigree Nomenclature Integrated with Biomedical Vocabularies},

author = {L Garcia-Giordano and S Paraiso-Medina and R Alonso-Calvo and F J Fern?ndez-Mart?nez and V Maojo},

year  = {2019},

date = {2019-01-01},

volume = {2019},

pages = {457--466},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{González-Durruthy2017,

title = {Carbon Nanotubes’ Effect on Mitochondrial Oxygen Flux Dynamics: Polarography Experimental Study and Machine Learning Models using Star Graph Trace Invariants of Raman Spectra},

author = {M González-Durruthy and J S Monserrat and B Rasulev and G M Casañola-Martin and J M Barreiro and S Paraiso-Medina and V Maojo and H Gonzalez-Diaz and A Pazos and C R Munteanu},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5707603/},

doi = {10.3390/nano7110386},

year  = {2017},

date = {2017-11-11},

journal = {Nanomaterials (Basel)},

volume = {7},

number = {11},

pages = {386},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid28982381,

title = {Querying clinical data in HL7 RIM based relational model with morph-RDB},

author = {F Priyatna and R Alonso-Calvo and S Paraiso-Medina and O Corcho},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5629785/},

year  = {2017},

date = {2017-01-01},

journal = {J Biomed Semantics},

volume = {8},

number = {1},

pages = {49},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid28802325b,

title = {SNOMED2HL7: A tool to normalize and bind SNOMED CT concepts to the HL7 Reference Information Model},

author = {D Perez-Rey and R Alonso-Calvo and S Paraiso-Medina and C R Munteanu and M Garcia-Remesal},

url = {https://www.ncbi.nlm.nih.gov/pubmed/28802325},

year  = {2017},

date = {2017-01-01},

journal = {Comput Methods Programs Biomed},

volume = {149},

pages = {1--9},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid28601027,

title = {A semantic interoperability approach to support integration of gene expression and clinical data in breast cancer},

author = {R Alonso-Calvo and S Paraiso-Medina and D Perez-Rey and E Alonso-Oset and R van Stiphout and S Yu and V Maojo },

url = {https://www.ncbi.nlm.nih.gov/pubmed/28601027},

year  = {2017},

date = {2017-01-01},

journal = { Computers in Biology and Medicine},

volume = {87},

pages = {179--186},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid27570644,

title = {Cohort Selection and Management Application Leveraging Standards-based Semantic Interoperability and a Groovy DSL},

author = {A Bucur and J van Leeuwen and N Z Chen and B Claerhout and K de Schepper and D Perez-Rey and S Paraiso-Medina and R Alonso-Calvo and K Mehta and C Krykwinski},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5001740/},

year  = {2016},

date = {2016-01-01},

journal = {AMIA Joint Summits on Translational Science Proceedings},

volume = {2016},

pages = {25--32},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid25248204,

title = {Semantic Normalization and Query Abstraction Based on SNOMED-CT and HL7: Supporting Multicentric Clinical Trials},

author = {S Paraiso-Medina and D Perez-Rey and A Bucur and B Claerhout and R Alonso-Calvo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/25248204},

year  = {2015},

date = {2015-05-01},

journal = {IEEE J Biomed Health Inform},

volume = {19},

number = {3},

pages = {1061-1067},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Alonso-Calvo2015,

title = {Enabling semantic interoperability in multi-centric clinical trials on breast cancer},

author = {R Alonso-Calvo and D Perez-Rey and S Paraiso-Medina and B Claerhout and P Hennebert and A Bucur},

doi = {https://doi.org/10.1016/j.cmpb.2015.01.003},

year  = {2015},

date = {2015-03-07},

journal = {Computed Methods and Programs in Biomedicine},

volume = {118},

number = {3},

pages = {322-329},

keywords = {},

pubstate = {published},

tppubtype = {article}

}