Identification of type 2 diabetes subgroups through topological analysis of patient similarity.
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Complex mechanisms linking neurocognitive dysfunction to insulin resistance and other metabolic dysfunctionOmics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism InvestigationsTranslational bioinformatics in the era of real-time biomedical, health care and wellness data streamsNetwork-Based Approach to Identify Potential Targets and Drugs that Promote Neuroprotection and Neurorepair in Acute Ischemic StrokeUncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysisLifestyle and precision diabetes medicine: will genomics help optimise the prediction, prevention and treatment of type 2 diabetes through lifestyle therapy?Topological Data Analysis Generates High-Resolution, Genome-wide Maps of Human Recombination.Use of big data in drug development for precision medicine.Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases.Phenome-Wide Association Studies as a Tool to Advance Precision Medicine.How Many Parameters Does It Take to Describe Disease Tolerance?Acridine Derivatives as Inhibitors of the IRE1α-XBP1 Pathway Are Cytotoxic to Human Multiple Myeloma.Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networksA personality trait contributes to the occurrence of postoperative delirium: a prospective studyDynamic modeling and network approaches for omics time course data: overview of computational approaches and applications.Integrating electronic health record genotype and phenotype datasets to transform patient careIn silico methods for drug repurposing and pharmacologyStress-impaired transcription factor expression and insulin secretion in transplanted human islets.Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records.NIH Precision Medicine Initiative: Implications for Diabetes Research.An informatics research agenda to support precision medicine: seven key areasInhibiting MicroRNA-503 and MicroRNA-181d with Losartan Ameliorates Diabetic Nephropathy in KKAy Mice.Identification of Topological Network Modules in Perturbed Protein Interaction Networks.Novel subgroups of attention-deficit/hyperactivity disorder identified by topological data analysis and their functional network modular organizationsMetabotyping and its application in targeted nutrition: an overview.Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspectiveThe Role of Gut-brain Axis in Regulating Glucose Metabolism After Acute Pancreatitis.Deep learning for healthcare: review, opportunities and challenges.Single-cell topological RNA-seq analysis reveals insights into cellular differentiation and development.New directions for diabetes prevention and management in behavioral medicine.Defining Glomerular Disease in Mechanistic Terms: Implementing an Integrative Biology Approach in Nephrology.EHR-based phenotyping: Bulk learning and evaluation.A method for identifying genetic heterogeneity within phenotypically defined disease subgroups.Patient Similarity: Emerging Concepts in Systems and Precision Medicine.Stratifying Patients with Diabetes into Clinically Relevant Groups by Combination of Chronic Conditions to Identify Gaps in Quality of Care.Precision medicine with electronic medical records: from the patients and for the patients.Glycated lysine-141 in haptoglobin improves the diagnostic accuracy for type 2 diabetes mellitus in combination with glycated hemoglobin HbA1c and fasting plasma glucoseAn electronic health record based model predicts statin adherence, LDL cholesterol, and cardiovascular disease in the United States Military Health System.Lost in Thought - The Limits of the Human Mind and the Future of Medicine.Prediction of Incident Hypertension Within the Next Year: Prospective Study Using Statewide Electronic Health Records and Machine Learning.
P2860
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P2860
Identification of type 2 diabetes subgroups through topological analysis of patient similarity.
description
2015 nî lūn-bûn
@nan
2015年の論文
@ja
2015年論文
@yue
2015年論文
@zh-hant
2015年論文
@zh-hk
2015年論文
@zh-mo
2015年論文
@zh-tw
2015年论文
@wuu
2015年论文
@zh
2015年论文
@zh-cn
name
Identification of type 2 diabe ...... nalysis of patient similarity.
@ast
Identification of type 2 diabe ...... nalysis of patient similarity.
@en
type
label
Identification of type 2 diabe ...... nalysis of patient similarity.
@ast
Identification of type 2 diabe ...... nalysis of patient similarity.
@en
prefLabel
Identification of type 2 diabe ...... nalysis of patient similarity.
@ast
Identification of type 2 diabe ...... nalysis of patient similarity.
@en
P2093
P2860
P1476
Identification of type 2 diabe ...... nalysis of patient similarity.
@en
P2093
Benjamin S Glicksberg
Joel T Dudley
Ronald Tamler
Wei-Yi Cheng
P2860
P304
P356
10.1126/SCITRANSLMED.AAA9364
P407
P577
2015-10-01T00:00:00Z