Finding potentially new multimorbidity patterns of psychiatric and somatic diseases: exploring the use of literature-based discovery in primary care research
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Erik M. van Mulligen | Marjan van den Akker | Rein Vos | Sil Aarts | Job Metsemakers | Martin P. van Boxtel | Frans Verhey | F. Verhey | E. V. Mulligen | M. Boxtel | J. Metsemakers | S. Aarts | M. Akker | R. Vos
[1] M. Roizen,et al. Examining a Bidirectional Association Between Depressive Symptoms and Diabetes , 2009 .
[2] Concetto Spampinato,et al. Combining literature text mining with microarray data: advances for system biology modeling , 2012, Briefings Bioinform..
[3] N R Smalheiser,et al. Using ARROWSMITH: a computer-assisted approach to formulating and assessing scientific hypotheses. , 1998, Computer methods and programs in biomedicine.
[4] J. A. Knottnerus,et al. In an exploratory prospective study on multimorbidity general and disease-related susceptibility could be distinguished. , 2006, Journal of clinical epidemiology.
[5] Sally Wyke,et al. Multimorbidity in primary care: a systematic review of prospective cohort studies. , 2012, The British journal of general practice : the journal of the Royal College of General Practitioners.
[6] Alan R. Powell,et al. Integration of text- and data-mining using ontologies successfully selects disease gene candidates , 2005, Nucleic acids research.
[7] Søren Brunak,et al. Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts , 2011, PLoS Comput. Biol..
[8] Barend Mons,et al. Assignment of protein function and discovery of novel nucleolar proteins based on automatic analysis of MEDLINE , 2007, Proteomics.
[9] A. Aronson. Filtering the UMLS ® Metathesaurus ® for MetaMap 1999 , 1991 .
[10] D. Swanson. Fish Oil, Raynaud's Syndrome, and Undiscovered Public Knowledge , 2015, Perspectives in biology and medicine.
[11] A. Tversky,et al. The framing of decisions and the psychology of choice. , 1981, Science.
[12] Michael R. Seringhaus,et al. Seeking a New Biology through Text Mining , 2008, Cell.
[13] William R. Hersh,et al. A Survey of Current Work in Biomedical Text Mining , 2005 .
[14] S. Wyke,et al. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study , 2012, The Lancet.
[15] Marc Weeber,et al. Case Report: Generating Hypotheses by Discovering Implicit Associations in the Literature: A Case Report of a Search for New Potential Therapeutic Uses for Thalidomide , 2003, J. Am. Medical Informatics Assoc..
[16] B Drewes. Integration Of Text And Data Mining , 2002 .
[17] S. Boyer,et al. Automatic mining of the literature to generate new hypotheses for the possible link between periodontitis and atherosclerosis: lipopolysaccharide as a case study. , 2007, Journal of clinical periodontology.
[18] 山田隆司. プライマリ ケア医のための疾病分類-International Classification of Primary Care (ICPC) , 1996 .
[19] T. Strine,et al. Prevalence of Depression Among U.S. Adults With Diabetes , 2008, Diabetes Care.
[20] S. Brunak,et al. Mining electronic health records: towards better research applications and clinical care , 2012, Nature Reviews Genetics.
[21] J A Knottnerus,et al. Multimorbidity in general practice: prevalence, incidence, and determinants of co-occurring chronic and recurrent diseases. , 1998, Journal of clinical epidemiology.
[22] Geert J. van Schendel,et al. Unlocking patients' records in general practice for research, medical education and quality assurance: the Registration Network Family Practices. , 1996, International journal of bio-medical computing.
[23] Ioannis G. Tollis,et al. SYMBIOmatics: Synergies in Medical Informatics and Bioinformatics – exploring current scientific literature for emerging topics , 2007, BMC Bioinformatics.
[24] A. Schatzberg,et al. Personality traits and medical outcome of cardiac illness. , 2010, Journal of psychiatric research.
[25] C E Lipscomb,et al. Medical Subject Headings (MeSH). , 2000, Bulletin of the Medical Library Association.
[26] B. Bentsen. International classification of primary care. , 1986, Scandinavian journal of primary health care.
[27] Saso Dzeroski,et al. Supporting Discovery in Medicine by Association Rule Mining in Medline and UMLS , 2001, MedInfo.
[28] B. Winblad,et al. Patterns of Chronic Multimorbidity in the Elderly Population , 2009, Journal of the American Geriatrics Society.
[29] Erik M. van Mulligen,et al. Constructing an associative concept space for literature-based discovery , 2004, J. Assoc. Inf. Sci. Technol..
[30] Marc Weeber,et al. Text-based discovery in biomedicine: the architecture of the DAD-system , 2000, AMIA.
[31] J. Jolles,et al. The relation between morbidity and cognitive performance in a normal aging population. , 1998, The journals of gerontology. Series A, Biological sciences and medical sciences.
[32] Padmini Srinivasan,et al. Mining MEDLINE for implicit links between dietary substances and diseases , 2004, ISMB/ECCB.
[33] David A. Hanauer,et al. Exploring Clinical Associations Using ‘-Omics’ Based Enrichment Analyses , 2009, PloS one.
[34] Trevor Cohen,et al. Reflective Random Indexing and indirect inference: A scalable method for discovery of implicit connections , 2010, J. Biomed. Informatics.
[35] J. Jolles,et al. Diabetes mellitus type II as a risk factor for depression: a lower than expected risk in a general practice setting , 2009, European Journal of Epidemiology.
[36] Marc Weeber,et al. Using concepts in literature-based discovery: Simulating Swanson's Raynaud-fish oil and migraine-magnesium discoveries , 2001, J. Assoc. Inf. Sci. Technol..
[37] Marc Weeber,et al. Using concepts in literature-based discovery: simulating Swanson's Raynaud-fish oil and migraine-magnesium discoveries , 2001 .
[38] E. Higgins,et al. Social psychology: Handbook of basic principles. , 1996 .
[39] Hendriek C Boshuizen,et al. Longitudinal administrative data can be used to examine multimorbidity, provided false discoveries are controlled for. , 2011, Journal of clinical epidemiology.
[40] A. Douzenis,et al. Medical comorbidity of cluster B personality disorders , 2012, Current opinion in psychiatry.
[41] Ştefan Boncu,et al. E. Tory Higgins si Arie Kruglanski (coord.), Social psychology. Handbook of basic principles, Guilford, New York, 1997 , 1998 .
[42] David B. Searls,et al. Can literature analysis identify innovation drivers in drug discovery? , 2009, Nature Reviews Drug Discovery.
[43] Richard W Grant,et al. Depression, Self-Care, and Medication Adherence in Type 2 Diabetes , 2007, Diabetes Care.
[44] D. Rebholz-Schuhmann,et al. Text-mining solutions for biomedical research: enabling integrative biology , 2012, Nature Reviews Genetics.
[45] Aaron M. Cohen,et al. Research Paper: A System for Classifying Disease Comorbidity Status from Medical Discharge Summaries Using Automated Hotspot and Negated Concept Detection , 2009, J. Am. Medical Informatics Assoc..
[46] M. Viana,et al. Clustering of psychiatric and somatic illnesses in the general population: multimorbidity and socioeconomic correlates. , 2010, Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas.
[47] Neil R. Smalheiser,et al. Literature-based discovery: Beyond the ABCs , 2012, J. Assoc. Inf. Sci. Technol..
[48] M. Schuemie,et al. Anni 2.0: a multipurpose text-mining tool for the life sciences , 2008, Genome Biology.
[49] E. Hovig,et al. GeneCount: genome-wide calculation of absolute tumor DNA copy numbers from array comparative genomic hybridization data , 2008, Genome Biology.
[50] P. Bork,et al. Literature mining for the biologist: from information retrieval to biological discovery , 2006, Nature Reviews Genetics.
[51] Katherine J Hoggatt,et al. Exploratory data mining analysis identifying subgroups of patients with depression who are at high risk for suicide. , 2009, The Journal of clinical psychiatry.
[52] Martijn J. Schuemie,et al. Novel Protein-Protein Interactions Inferred from Literature Context , 2009, PloS one.
[53] George Hripcsak,et al. Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study. , 2008, Journal of the American Medical Informatics Association : JAMIA.
[54] E. Higgins. Knowledge activation: Accessibility, applicability, and salience. , 1996 .
[55] Erik M. van Mulligen,et al. Research for research: tools for knowledge discovery and visualization , 2002, AMIA.
[56] Marjan van den Akker,et al. Multimorbidity's many challenges , 2007, BMJ : British Medical Journal.
[57] Padmini Srinivasan,et al. Exploring text mining from MEDLINE , 2002, AMIA.
[58] Martijn J. Schuemie,et al. Literature-based concept profiles for gene annotation: The issue of weighting , 2008, Int. J. Medical Informatics.
[59] Padmini Srinivasan,et al. MeSHmap: a text mining tool for MEDLINE , 2001, AMIA.
[60] David J. Sheskin,et al. Handbook of Parametric and Nonparametric Statistical Procedures , 1997 .
[61] Michael A. Becker. Social Psychology: Handbook of Basic Principles , 1998 .
[62] M. V. van Boxtel,et al. Influence of multimorbidity on cognition in a normal aging population: a 12‐year follow‐up in the Maastricht Aging Study , 2011, International journal of geriatric psychiatry.
[63] S. Kunitz. Holism and the idea of general susceptibility to disease. , 2002, International journal of epidemiology.