Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients
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Conditional Disease Development extracted from Longitudinal Health Care Cohort Data using Layered Network Construction.Advances in understanding COPDPhysical Trauma and Amyotrophic Lateral Sclerosis: A Population-Based Study Using Danish National RegistriesAnalysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared lociThe human disease network in terms of dysfunctional regulatory mechanismsPatient healthcare trajectory. An essential monitoring tool: a systematic review.Analysis of free text in electronic health records for identification of cancer patient trajectories.THE TRAINING OF NEXT GENERATION DATA SCIENTISTS IN BIOMEDICINEFrom comorbidities of chronic obstructive pulmonary disease to identification of shared molecular mechanisms by data integration.Klinefelter syndrome comorbidities linked to increased X chromosome gene dosage and altered protein interactome activityHow to build personalized multi-omics comorbidity profilesDNetDB: The human disease network database based on dysfunctional regulation mechanismComparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networksComorbidity Analysis According to Sex and Age in Hypertension Patients in ChinaDiagnosis trajectories of prior multi-morbidity predict sepsis mortality.eHealth provides a novel opportunity to exploit the advantages of the Nordic countries in psychiatric genetic research, building on the public health care system, biobanks, and registries.Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank.Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspectiveBiomechanisms of Comorbidity: Reviewing Integrative Analyses of Multi-omics Datasets and Electronic Health Records.Protein function in precision medicine: deep understanding with machine learning.Chronic obstructive pulmonary disease phenotypes using cluster analysis of electronic medical records.Mobile health: the power of wearables, sensors, and apps to transform clinical trials.Network-based analysis of diagnosis progression patterns using claims data.Why and how are we living longer?Chronic Obstructive Pulmonary Disease (COPD) as a disease of early aging: Evidence from the EpiChron Cohort.Opportunities and obstacles for deep learning in biology and medicine.Identifying temporal patterns in patient disease trajectories using dynamic time warping: A population-based study.Mining co-occurrence and sequence patterns from cancer diagnoses in New York State.A Systems Approach to Refine Disease Taxonomy by Integrating Phenotypic and Molecular Networks.Big data from electronic health records for early and late translational cardiovascular research: challenges and potential.Risk and temporal order of disease diagnosis of comorbidities in patients with COPD: a population health perspective.Disease networks identify specific conditions and pleiotropy influencing multimorbidity in the general populationThe heart of the matter: in search of causal effects of depression on somatic diseasesUsing predicate and provenance information from a knowledge graph for drug efficacy screeningPergola: Boosting Visualization and Analysis of Longitudinal Data by Unlocking Genomic Analysis ToolsStatistical methods for constructing disease comorbidity networks from longitudinal inpatient data
P2860
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P2860
Temporal disease trajectories condensed from population-wide registry data covering 6.2 million patients
description
2014 nî lūn-bûn
@nan
2014 թուականի Յունիսին հրատարակուած գիտական յօդուած
@hyw
2014 թվականի հունիսին հրատարակված գիտական հոդված
@hy
2014年の論文
@ja
2014年論文
@yue
2014年論文
@zh-hant
2014年論文
@zh-hk
2014年論文
@zh-mo
2014年論文
@zh-tw
2014年论文
@wuu
name
Temporal disease trajectories ...... covering 6.2 million patients
@ast
Temporal disease trajectories ...... covering 6.2 million patients
@en
type
label
Temporal disease trajectories ...... covering 6.2 million patients
@ast
Temporal disease trajectories ...... covering 6.2 million patients
@en
prefLabel
Temporal disease trajectories ...... covering 6.2 million patients
@ast
Temporal disease trajectories ...... covering 6.2 million patients
@en
P2093
P2860
P50
P3181
P356
P1476
Temporal disease trajectories ...... covering 6.2 million patients
@en
P2093
Henriette Schmock
Pope L. Moseley
Robert Eriksson
Sabrina Gade Ellesøe
Tudor I. Oprea
P2860
P2888
P3181
P356
10.1038/NCOMMS5022
P407
P577
2014-06-24T00:00:00Z
P5875
P6179
1049117594