Scientific Publications

@article{nokey,

title = {Impact of COVID-19 in patients with multiple myeloma based on a global data network},

author = {J Martinez-Lopez and G Hernandez-Ibarburu and R Alonso and J M Sanchez-Pina and I Zamanillo and N Lopez-Muñoz and Rodrigo Iñiguez and C Cuellar and M Calbacho and M L Paciello and R Ayala and N García-Barrio and D Perez-Rey and L Meloni and J Cruz and M Pedrera-Jiménez and P Serrano-Balazote & J de la Cruz },

editor = {Nature Publishing Group},

url = {https://www.nature.com/articles/s41408-021-00588-z#citeas},

doi = {https://doi.org/10.1038/s41408-021-00588-z},

issn = {2044-5385},

year  = {2021},

date = {2021-12-10},

journal = {Blood Cancer Journal},

volume = {11},

abstract = {The COVID-19 pandemic has represented a major cause of morbidity/mortality worldwide, overstressing health systems. Multiple myeloma (MM) patients show an increased risk for infections and they are expected to be particularly vulnerable to SARS-CoV-2 infection. Here we have obtained a comprehensive picture of the impact of COVID-19 in MM patients on a local and a global scale using a federated data research network (TriNetX) that provided access to Electronic Medical Records (EMR) from Health Care Organizations (HCO) all over the world. Through propensity score matched analyses we found that the number of new diagnoses of MM was reduced in 2020 compared to 2019 (RR 0.86, 95%CI 0.76–0.96) and the survival of newly diagnosed MM cases decreased similarly (HR 0.61, 0.38–0.81). MM patients showed higher risk of SARS-CoV-2 infection (RR 2.09, 1.58–2.76) and a higher excess mortality in 2020 (difference in excess mortality 9%, 4.4–13.2) than non-MM patients. By interrogating large EMR datasets from HCO in Europe and globally, we confirmed that MM patients have been more severely impacted by COVID-19 pandemic than non-MM patients. This study highlights the necessity of extending preventive measures worlwide to protect vulnerable patients from SARS-CoV-2 infection by promoting social distancing and an intensive vaccination strategies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CARRACEDOREBOREDO20214538,

title = {A review on machine learning approaches and trends in drug discovery},

author = {Paula Carracedo-Reboredo and Jose Liñares-Blanco and Nereida Rodríguez-Fernández and Francisco Cedrón and Francisco J Novoa and Adrian Carballal and V Maojo and A Pazos and C Fernandez-Lozano},

editor = {Research Network of Computational and Structural Biotechnology},

url = {https://www.sciencedirect.com/science/article/pii/S2001037021003421},

doi = {https://doi.org/10.1016/j.csbj.2021.08.011},

issn = {2001-0370},

year  = {2021},

date = {2021-08-12},

urldate = {2021-08-12},

journal = {Computational and Structural Biotechnology Journal},

volume = {19},

pages = {4538-4558},

abstract = {Drug discovery aims at finding new compounds with specific chemical properties for the treatment of diseases. In the last years, the approach used in this search presents an important component in computer science with the skyrocketing of machine learning techniques due to its democratization. With the objectives set by the Precision Medicine initiative and the new challenges generated, it is necessary to establish robust, standard and reproducible computational methodologies to achieve the objectives set. Currently, predictive models based on Machine Learning have gained great importance in the step prior to preclinical studies. This stage manages to drastically reduce costs and research times in the discovery of new drugs. This review article focuses on how these new methodologies are being used in recent years of research. Analyzing the state of the art in this field will give us an idea of where cheminformatics will be developed in the short term, the limitations it presents and the positive results it has achieved. This review will focus mainly on the methods used to model the molecular data, as well as the biological problems addressed and the Machine Learning algorithms used for drug discovery in recent years.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CIDMEJIAS2021105958,

title = {A deep learning approach using synthetic images for segmenting and estimating 3D orientation of nanoparticles in EM images},

author = {A Cid-Mejías and R Alonso-Calvo and H Gavilán and J Crespo and V Maojo},

editor = {Elsevier},

url = {https://www.sciencedirect.com/science/article/pii/S016926072100033X},

doi = {https://doi.org/10.1016/j.cmpb.2021.105958},

issn = {0169-2607},

year  = {2021},

date = {2021-04-01},

journal = {Computer Methods and Programs in Biomedicine},

volume = {202},

abstract = {Background and objective: Nanoparticles present properties that can be applied to a wide range of fields such as biomedicine, electronics or optics. The type of properties depends on several characteristics, being some of them related with the particle structure. A proper characterization of nanoparticles is crucial since it could affect their applications. To characterize a particle shape and size, the nanotechnologists employ Electron Microscopy (EM) to obtain images of nanoparticles and perform measures over them. This task could be tedious, repetitive and slow, we present a Deep Learning method based on Convolutional Neural Networks (CNNs) to detect, segment, infer orientations and reconstruct microscope images of nanoparticles. Since machine learning algorithms depend on annotated data and there is a lack of annotated datasets of nanoparticles, our work makes use of artificial datasets of images resembling real nanoparticles photographs. Methods: Our work is divided into three tasks. Firstly, a method to create annotated datasets of artificial images resembling Scanning Electron Microscope (SEM). Secondly, two models of convolutional neural networks are trained using the artificial datasets previously generated, the first one is in charge of the detection and segmentation of the nanoparticles while the second one will infer the nanoparticle orientation. Finally, the 3D reconstruction module will recreate in a 3D scene the set of detected particles. Results: We have tested our method with five different shapes of basic nanoparticles: spheres, cubes, ellipsoids, hexagonal discs and octahedrons. An analysis of the reconstructions was conducted by manually comparing each of them with the real images. The results obtained have been promising, the particles are segmented and reconstructed accordingly to their shapes and orientations. Conclusions: We have developed a method for nanoparticle detection and segmentation in microscope images. Moreover, we can also infer an approximation of the 3D orientation of the particles and, in conjunction with the detections, create a 3D reconstruction of the photographs. The novelty of our approximation lies in the dataset used. Instead of using annotated images, we have created the datasets simulating the microscope images by using basic geometrical objects that imitate real nanoparticles.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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{MILLANFERNANDEZMONTES2020103519,

title = {Mapping clinical procedures to the ICD-10-PCS: The German operation and procedure classification system use case},

author = {A Millan-Fernandez-Montes and D Perez-Rey and G Hernandez-Ibarburu and MB Palchuk and C Muelle and B Claerhout},

editor = {Academic Press},

url = {https://www.sciencedirect.com/science/article/pii/S1532046420301477},

doi = {https://doi.org/10.1016/j.jbi.2020.103519},

issn = {1532-0464},

year  = {2020},

date = {2020-09-01},

urldate = {2020-09-01},

journal = {Journal of Biomedical Informatics},

volume = {109},

abstract = {ICD-10-PCS, Lexical matching, Mapping methodology, OPS, Clinical procedures, EHR},

Mappings among terminologies to ensure homogeneous analysis among different data sources is one of the key challenges of semantic interoperability. Concretely, mappings to the International Classification of Diseases 10th Revision Procedure Classification System (ICD-10-PCS) are especially challenging due to its multiaxial structure and lack of terms used by physicians (many terminologies used in real world data (RWD) are initially intended for reimbursement, not for clinical purposes). In this work, we propose a new theoretical methodology for mapping healthcare data to the ICD-10-PCS by exploiting its multiaxial structure to reduce the search spaces within concepts and leveraging the dependencies between axes for inferring additional relevant information. We tested this methodology with a subset of the German Operation and Procedure Classification System (OPS), aiming to integrate heterogeneous data sources queried for clinical research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{HERNANDEZIBARBURU2019189,

title = {ICD-10-CM extension with ICD-9 diagnosis codes to support integrated access to clinical legacy data},

author = {G Hernandez-Ibarburu and D Perez-Rey and E Alonso-Oset and R Alonso-Calvo and [de K Schepper] and L Meloni and B Claerhout},

url = {http://www.sciencedirect.com/science/article/pii/S1386505619301972},

doi = {https://doi.org/10.1016/j.ijmedinf.2019.06.010},

issn = {1386-5056},

year  = {2019},

date = {2019-01-01},

journal = {International Journal of Medical Informatics},

volume = {129},

pages = {189 - 197},

abstract = {Introduction 

ICD is currently the most widely used terminology to code diagnosis and procedures. The transition from ICD-9-CM to ICD-10-CM became effective on October 1, 2015 in US and many other countries. Projects that use this codification for research purposes, requires advanced methods to exploit data with both versions of ICD. Although the General Equivalence Mappings (GEMs), provided by the Centers for Medicare and Medicaid Services, might help to overcome these challenges, their direct use as translation mappings is not possible, mostly due to the further specificity of ICD-10-CM concepts. 

Objective 

We propose a methodology to generate an extended version of ICD-10-CM with selected ICD-9-CM diagnosis codes. 

Methods 

The extension was generated using the GEMs relations between concepts of both terminologies and the hierarchical relations of ICD-10-CM. 

Results 

This extended ICD-10-CM, together with modifications to the mapping of ICD-9-CM concepts that were not inserted, allows the generation of an improved translation of legacy data, raising the number of 1-to-1 correspondences by +13.81%. 

Conclusion 

The extended ICD-10-CM enables the accurate integration of ICD-9-CM and ICD-10-CM diagnosis data into a single terminology. With such analysis of data possible without having to specify both ICD-9-CM and ICD-10-CM separately for each query.},

keywords = {clinical terminologies, component, data integration, ICD-10, ICD-9, interoperability},

pubstate = {published},

tppubtype = {article}

}

@article{HERNANDEZIBARBURU201970,

title = {ICD-10-PCS extension with ICD-9 procedure codes to support integrated access to clinical legacy data},

author = {G Hernandez-Ibarburu and D Perez-Rey and E Alonso-Oset and R Alonso-Calvo and D Voets and C Mueller and B Claerhout and N V Custodix},

url = {http://www.sciencedirect.com/science/article/pii/S1386505618302181},

doi = {https://doi.org/10.1016/j.ijmedinf.2018.11.002},

issn = {1386-5056},

year  = {2019},

date = {2019-01-01},

journal = {International Journal of Medical Informatics},

volume = {122},

pages = {70 - 79},

abstract = {Since the creation of The International Classification of Diseases (ICD), new versions have been released to keep updated with the current medical knowledge. Migrations of Electronic Health Records (EHR) from ICD-9 to ICD-10-PCS as clinical procedure codification system, has been a significant challenge and involved large resources. In addition, it created new barriers for integrated access to legacy medical procedure data (frequently ICD-9 coded) with current data (frequently ICD-10-PCS coded). This work proposes a solution based on extending ICD-10-PCS with a subgroup of ICD-9-CM concepts to facilitate such integrated access. The General Equivalence Mappings (GEMs) has been used as foundation to set the terminology relations of these inserted concepts in ICD-10-PCS hierarchy, but due to the existence of 1-to-many mappings, advanced rules are required to seamlessly integrate both terminologies. With the generation of rules based on GEMs relationships, 2014 ICD-9 concepts were included within the ICD-10-PCS hierarchy. For the rest of the concepts, a new method is also proposed to increase 1-to-1 mappings. As results, with the suggested approach, the percentage of ICD-9-CM procedure concepts that can be mapped accurately (avoiding mappings to a large number of concepts) rise from 11.56% to 69.01% of ICD-9-Proc, through the extended ICD-10-PCS hierarchy.},

keywords = {clinical terminologies, component, data integration, ICD-10, ICD-9, interoperability},

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{hernandez2018icd,

title = {ICD-10-PCS Extension with ICD-9 Procedure Codes to Support Integrated Access to Clinical Legacy Data},

author = {G Hernandez-Ibarburu and D Perez-Rey and E Alonso-Oset and R Alonso-Calvo and D Voets and C Mueller and B Claerhout},

doi = {https://doi.org/10.1016/j.ijmedinf.2018.11.002},

year  = {2018},

date = {2018-11-16},

journal = {International Journal of Medical Informatics},

abstract = {Since the creation of The International Classification of Diseases (ICD), new versions have been released to keep updated with the current medical knowledge. Migrations of Electronic Health Records (EHR) from ICD-9 to ICD-10-PCS as clinical procedure codification system, has been a significant challenge and involved large resources. In addition, it created new barriers for integrated access to legacy medical procedure data (frequently ICD-9 coded) with current data (frequently ICD-10-PCS coded). This work proposes a solution based on extending ICD-10-PCS with a subgroup of ICD-9-CM concepts to facilitate such integrated access. The General Equivalence Mappings (GEMs) has been used as foundation to set the terminology relations of these inserted concepts in ICD-10-PCS hierarchy, but due to the existence of 1-to-many mappings, advanced rules are required to seamlessly integrate both terminologies. With the generation of rules based on GEMs relationships, 2,014 ICD-9 concepts were included within the ICD-10-PCS hierarchy. For the rest of the concepts, a new method is also proposed to increase 1-to-1 mappings. As results, with the suggested approach, the percentage of ICD-9-CM procedure concepts that can be mapped accurately (avoiding mappings to a large number of concepts) rise from 11.56% to 69.01% of ICD-9-Proc, through the extended ICD-10-PCS hierarchy.},

keywords = {clinical terminologies, component, data integration, ICD-10, ICD-9, interoperability},

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{pmid28092493b,

title = {Enhancing Collaborative Case Diagnoses Through Unified Medical Language System-Based Disambiguation: A Case Study of the Zika Virus},

author = {A Moreira and R Alonso-Calvo and A Muñoz and J Crespo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/28092493},

year  = {2017},

date = {2017-07-01},

journal = {Telemed J E Health},

volume = {23},

number = {7},

pages = {608--614},

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{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{pmid28119991,

title = {Research Strategies for Biomedical and Health Informatics. Some Thought-provoking and Critical Proposals to Encourage Scientific Debate on the Nature of Good Research in Medical Informatics},

author = {R Haux and C A Kulikowski and S Bakken and S de Lusignan and M Kimura and S Koch and J Mantas and V Maojo and M Marschollek and F Martin-Sanchez and A Moen and H A Park and I N Sarkar and T Y Leong and A T McCray},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5388922/},

year  = {2017},

date = {2017-01-01},

journal = {Methods Inf Med},

volume = {56},

pages = {1-10},

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{pmid27224847,

title = {The INTEGRATE project: Delivering solutions for efficient multi-centric clinical research and trials},

author = {H Kondylakis and B Claerhout and M Keyur and L Koumakis and J van Leeuwen and K Marias and D Perez-Rey and K De Schepper and M Tsiknakis and A Bucur},

url = {https://www.ncbi.nlm.nih.gov/pubmed/27224847},

year  = {2016},

date = {2016-08-11},

journal = {J Biomed Inform},

volume = {62},

pages = {32--47},

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{pmid27524112,

title = {Discussion of "The New Role of Biomedical Informatics in the Age of Digital Medicine"},

author = {N Al-Shorbaji and R Bellazzi and F Gonzalez Bernaldo de Quiros and S Koch and CA Kulikowski and NH Lovell and V Maojo and HA Park and IN Sarkar and H Tanaka},

url = {https://www.ncbi.nlm.nih.gov/pubmed/27524112},

year  = {2016},

date = {2016-01-01},

journal = {Methods Inf Med},

volume = {55},

number = {5},

pages = {403--421},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid26873780,

title = {A method and software framework for enriching private biomedical sources with data from public online repositories},

author = {A Anguita and M Garcia-Remesal and N Graf and V Maojo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/26873780},

year  = {2016},

date = {2016-01-01},

journal = {J Biomed Inform},

volume = {60},

pages = {177--186},

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}

}

@article{pmid25072377b,

title = {Towards the taxonomic categorization and recognition of nanoparticle shapes},

author = {M Munoz-Marmol and J Crespo and M J Fritts and V Maojo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/25072377},

year  = {2015},

date = {2015-02-01},

journal = {Nanomedicine},

volume = {11},

number = {2},

pages = {457--465},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Filippini2015,

title = {I®ML: An infrastructure Resilience-Oriented modeling language},

author = {R Filippini and A Silva},

url = {http://dx.doi.org/10.1109/tsmc.2014.2343751 },

year  = {2015},

date = {2015-01-13},

journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems},

volume = {45},

number = {1},

pages = {157-169},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid24777240,

title = {Toward a view-oriented approach for aligning RDF-based biomedical repositories},

author = {A Anguita and M Garcia-Remesal and D de la Iglesia and N Graf and V Maojo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/24777240},

year  = {2015},

date = {2015-01-01},

journal = {Methods Inf Med},

volume = {54},

number = {1},

pages = {50-55},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid26306242,

title = {Case Study for Integration of an Oncology Clinical Site in a Semantic Interoperability Solution based on HL7 v3 and SNOMED-CT: Data Transformation Needs},

author = {A Ibrahim and A Bucur and D Perez-Rey and E Alonso-Oset and M de Hoog and A Dekker and M S Marshall},

url = {https://www.ncbi.nlm.nih.gov/pubmed/26306242},

year  = {2015},

date = {2015-01-01},

journal = {ÄMIA Jt Summits Transl Sci Proc},

volume = {2015},

pages = {71},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid24952607,

title = {Past and next 10 years of medical informatics},

author = {F Uckert and E Ammenwerth and C Dujat and A Grant and R Haux and A Hein and A Hochlehnert and P Knaup-Gregori and C Kulikowski and J Mantas and V Maojo and M Marschollek and L Moura and M Plischke and R Rohrig and J Stausberg and K Takabayashi and A Winter and KH Wolf and A Hasman},

url = {https://www.ncbi.nlm.nih.gov/pubmed/24952607},

year  = {2014},

date = {2014-07-01},

journal = {J Med Syst},

volume = {38},

number = {7},

pages = {74},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid24952606,

title = {Assessing the prognoses on Health care in the information society 2013 - thirteen years after},

author = {P Knaup and E Ammenwerth and C Dujat and A Grant and A Hasman and A Hein and A Hochlehnert and C Kulikowski and J Mantas and V Maojo and M Marschollek and L Moura and M Plischke and R Rohrig and J Stausberg and K Takabayashi and F Uckert and A Winter and K H Wolf and R Haux},

url = {https://www.ncbi.nlm.nih.gov/pubmed/24952606},

year  = {2014},

date = {2014-07-01},

journal = {J Med Syst},

volume = {38},

number = {7},

pages = {73},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Filippini2014,

title = {A modeling framework for the resilience analysis of networked systems-of-systems based on functional dependencies},

author = {R Filippini and A Silva},

url = {http://linkinghub.elsevier.com/retrieve/pii/S0951832013002676},

year  = {2014},

date = {2014-05-14},

journal = {Reliability Engineering & System Safety},

volume = {125},

pages = {82-91},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Diez2014,

title = {Resilience of Cloud Computing in Critical Systems},

author = {O Diez and A Silva},

url = {http://onlinelibrary.wiley.com/doi/10.1002/qre.1579/abstract;jsessionid=9B96F369434E895AB71194B344C9D771.f02t03},

year  = {2014},

date = {2014-04-06},

journal = {Quality and Reliability Engineering International},

volume = {30},

number = {3},

pages = {397-412},

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@article{pmid25347075,

title = {A machine learning approach to identify clinical trials involving nanodrugs and nanodevices from ClinicalTrials.gov.},

author = {D de la Iglesia and M Garcia-Remesal and A Anguita and M Munoz-Marmol and C Kulikowski and V Maojo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/25347075},

year  = {2014},

date = {2014-01-01},

journal = {PLoS ONE},

volume = {9},

number = {10},

pages = {e110331},

keywords = {},

pubstate = {published},

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@article{pmid25160302b,

title = {Supporting patient screening to identify suitable clinical trials},

author = {A Bucur and J Van Leeuwen and N Z Chen and B Claerhout and K De Schepper and D Perez-Rey and R Alonso-Calvo and L Pugliano and K Saini},

url = {https://www.ncbi.nlm.nih.gov/pubmed/25160302},

year  = {2014},

date = {2014-01-01},

journal = {Stud Health Technol Inform},

volume = {205},

pages = {823--827},

keywords = {},

pubstate = {published},

tppubtype = {article}

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@article{pmid23876373,

title = {Note on Friedman's 'what informatics is and isn't'},

author = {V Maojo and C A Kulikowski},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3861923/},

year  = {2013},

date = {2013-12-01},

journal = {Journal of the American Medial Informatics Association},

volume = {20},

number = {e2},

pages = {e365--366},

keywords = {},

pubstate = {published},

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@article{pmid24932210,

title = {Nanoinformatics knowledge infrastructures: bringing efficient information management to nanomedical research},

author = {D de la Iglesia and R E Cachau and M Garcia-Remesal and V Maojo},

url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053539/},

year  = {2013},

date = {2013-11-01},

journal = {Comput Sci Discov},

volume = {6},

number = {1},

pages = {014011},

keywords = {},

pubstate = {published},

tppubtype = {article}

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@article{pmid23808970,

title = {Improving data and knowledge management to better integrate health care and research},

author = {M Cases and L I Furlong and J Albanell and R B Altman and R Bellazzi and S Boyer and A Brand and A J Brookes and S Brunak and T W Clark and J Gea and P Ghazal and N Graf and R Guigo and T E Klein and N Lopez-Bigas and V Maojo and B Mons and M Musen and J L Oliveira and A Rowe and P Ruch and A Shabo and E H Shortliffe and A Valencia and J van der Lei and M A Mayer and F Sanz},

url = {https://www.ncbi.nlm.nih.gov/pubmed/23808970},

year  = {2013},

date = {2013-10-18},

journal = {J. Intern. Med.},

volume = {274},

number = {4},

pages = {321--328},

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@article{pmid23669178b,

title = {RDFBuilder: a tool to automatically build RDF-based interfaces for MAGE-OM microarray data sources},

author = {A Anguita and M Garcia-Remesal and V Maojo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/23669178},

year  = {2013},

date = {2013-07-01},

journal = {Comput Methods Programs Biomed},

volume = {111},

number = {1},

pages = {220--227},

keywords = {},

pubstate = {published},

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@article{pmid23698436,

title = {Funding: Campaign tactics and grants don't mix},

author = {V Maojo and J Pazos and C A Kulikowski},

url = {https://www.nature.com/nature/journal/v497/n7450/full/497439b.html},

year  = {2013},

date = {2013-05-01},

journal = {Nature},

volume = {497},

number = {7450},

pages = {439},

keywords = {},

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@article{Diez2013,

title = {Govcloud: Using cloud computing in public organizations},

author = {O Diez and A Silva},

url = {http://dx.doi.org/10.1109/mts.2013.2241473},

year  = {2013},

date = {2013-03-13},

journal = {IEEE Technology and Society Magazine},

volume = {32},

number = {1},

pages = {66-72},

keywords = {},

pubstate = {published},

tppubtype = {article}

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@article{pmid23548020b,

title = {The impact of computer science in molecular medicine: enabling high-throughput research},

author = {D de la Iglesia and M Garcia-Remesal and G de la Calle and C Kulikowski and F Sanz and V Maojo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/23548020},

year  = {2013},

date = {2013-01-01},

journal = {Curr Top Med Chem},

volume = {13},

number = {5},

pages = {526--575},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid23509721b,

title = {Using nanoinformatics methods for automatically identifying relevant nanotoxicology entities from the literature},

author = {M Garcia-Remesal and A Garcia-Ruiz and D Perez-Rey and D de la Iglesia and V Maojo},

url = {https://www.ncbi.nlm.nih.gov/pubmed/23509721},

year  = {2013},

date = {2013-01-01},

journal = {Biomed Res Int},

volume = {2013},

pages = {410294},

keywords = {},

pubstate = {published},

tppubtype = {article}

}