Page Index - sporedata/researchdesigneR GitHub Wiki

1385 page(s) in this GitHub Wiki:

• Home
• #00.Datasets
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• #01.Association
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• #02.Causation
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• #03.Computer vision
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• #04.Data collection
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• #05.Data linkage
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• #06.Diagnostics
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• #07.Health economics
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• #08.Latent variable modeling
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• #09.Machine learning
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• #10.Natural language processing
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• #11.Meta analysis
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• #12.Operations
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• #13.Qualitative
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• #14.Randomization
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• #15.Sensors
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• #16.Social network analysis
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• #17.Spatial analysis
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• #18.Time series
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• #19.Visualization
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• #20.Important research QA and information
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• #21.Reporting Guidelines
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• 00.Datasets01 (A C)
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• 00.Datasets02 (D L)
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• 00.Datasets03 (M R)
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• 00.Datasets04 (S Z)
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• 01.Association.Pre requisites for association
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• 01.Association01.Exploratory analysis
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• 01.Association02.Inferential tests
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• 01.Association03.Models for outcomes measured a single time
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• 01.Association04.Models with grouped outcomes
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• 01.Association05.Time to event
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• 01.Association06.Genetic association studies
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• 01.Association07.Attributable fraction, number needed to treat, and relative excess risk due to interaction
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• 01.Association08.Missing data
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• 01.Association09.Measuring change scores
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• 01.Association10.Observer agreement
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• 01.Association11.Dose response analysis
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• 01.Association12.Multiple comparisons
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• 01.Association13.Decomposition methods
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• 01.Association14.Copula models
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• 01.Association15.Sensitivity analysis
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• 02.Causation.Common references for causation
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• 02.Causation.Pre requisites for causal analysis
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• 02.Causation01.Causal Bayesian networks
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• 02.Causation02.Difference in differences
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• 02.Causation03.Instrumental variables
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• 02.Causation04a.Heterogeneity of effect subgroup analysis
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• 02.Causation04b.Mediation and moderation analyses
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• 02.Causation05.Propensity scores
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• 02.Causation06.Regression discontinuity design
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• 02.Causation07.Causal machine learning
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• 02.Causation08.Interrupted time series
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• 02.Causation09.Target trial emulation
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• 03.Computer Vision.Pre requisites for computer vision
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• 03.Computer Vision01.Image detection and classification
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• 03.Computer Vision02.Image segmentation
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• 04.Data collection.Pre requisites for data collection
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• 04.Data collection01.Chatbot
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• 04.Data collection02.Interviews and focus groups
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• 04.Data collection03.Mechanical Turk
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• 04.Data collection04.Email surveys
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• 04.Data collection05.Registry
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• 04.Data collection06.Trial
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• 04.Data collection07.Patient data donation
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• 04.Data collection08.Platform trials
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• 04.Data collection09.Data quality control
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• 04.Data collection10.Design and data coordination center
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• 04.Data collection11.Sampling
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• 05.Data linkage.Pre requisites for data linkage
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• 05.Data linkage01.Probabilistic
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• 05.Data linkage02.Linkage by geolocation
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• 05.Data linkage03.Statistical matching
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• 05.Data linkage04.Enrichment by machine learning
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• 06.Diagnostics.Pre requisites for diagnostics
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• 06.Diagnostics01.Diagnostic properties
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• 06.Diagnostics02.Screening studies
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• 07.Health economics.Common packages for health economics
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• 07.Health economics.Pre requisites for health economics
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• 07.Health economics01.Cost utility analysis
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• 07.Health economics02.Discrete choice experiments
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• 07.Health economics03.Individualized cost effectiveness analysis
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• 07.Health economics04.Value of information analysis
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• 08.Latent variable modeling.Common references for latent variable modeling
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• 08.Latent variable modeling.Pre requisites for latent variable modeling
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• 08.Latent variable modeling01.Factor analysis
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• 08.Latent variable modeling02.Validity
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• 08.Latent variable modeling03.Internal reliability
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• 08.Latent variable modeling04.Item response theory
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• 08.Latent variable modeling05.Latent class modeling
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• 08.Latent variable modeling06.Structural equation modeling
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• 08.Latent variable modeling07.Minimal clinically important difference
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• 08.Latent variable modeling08.Computerized adaptive testing
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• 09.Machine learning.Common references for machine learning
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• 09.Machine learning.Pre requisites for machine learning
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• 09.Machine learning01.Classification
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• 09.Machine learning02.Regression
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• 09.Machine learning03.Survival
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• 09.Machine learning04.Time series
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• 09.Machine learning05.Causation
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• 09.Machine learning06.Clustering
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• 09.Machine learning07.Model transfer
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• 09.Machine learning08.Microsimulation
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• 09.Machine learning09.Recommender systems
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• 09.Machine learning10.Clinical decision support systems
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• 09.Machine learning11.Sensor driven
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• 09.Machine learning12. Reinforcement learning
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• 10.Natural language processing.Common packages for natural language processing
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• 10.Natural language processing.Common references for natural language processing
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• 10.Natural language processing.Pre requisites for natural language processing
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• 10.Natural language processing01.Extraction and classification
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• 10.Natural language processing02.Sentiment analysis
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• 11.Meta analysis.Pre requisites for meta analysis
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• 11.Meta analysis01.Diagnostic
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• 11.Meta analysis02.Individual participants
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• 11.Meta analysis03.Observational studies
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• 11.Meta analysis04.Randomized trials
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• 11.Meta analysis05.Qualitative studies
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• 11.Meta analysis06.Scales
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• 11.Meta analysis07.Network meta analysis
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• 11.Meta analysis08.Scoping reviews
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• 11.Meta analysis09.Rapid
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• 11.Meta analysis10.Realist
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• 11.Meta analysis11.Pragmatic
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• 11.Meta analysis12.Meta meta analysis
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• 11.Meta analysis13.Mapping
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• 11.Meta analysis14.Scanning the horizon
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• 12.Operations.Pre requisites for operations
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• 12.Operations01.Discrete event simulation
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• 12.Operations02.Agent based modeling
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• 12.Operations03.System dynamics
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• 12.Operations04.Differential equation modeling
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• 12.Operations05.Event sequence (memoryless)
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• 13.Qualitative.Common references for qualitative research
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• 13.Qualitative.Pre requisites for qualitative research
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• 13.Qualitative01.Cognitive task analysis
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• 13.Qualitative02.Implementation science
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• 13.Qualitative03.Mixed methods design
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• 13.Qualitative04.Shared decision making
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• 13.Qualitative05.Case studies
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• 13.Qualitative06.Participatory research
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• 13.Qualitative07.Coincidence Analysis (CNA)
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• 13.Qualitative08.Text analysis
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• 13.Qualitative09.Delphi
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• 14.Randomization.Common references for randomized designs
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• 14.Randomization.Pre requisites for randomized designs
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• 14.Randomization01.Adaptive enrichment design
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• 14.Randomization02.Bayesian adaptive
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• 14.Randomization03.Cluster
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• 14.Randomization04.Cluster Stepped Wedge
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• 14.Randomization05.Cross over
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• 14.Randomization06.N of 1
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• 14.Randomization07.Non inferiority
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• 14.Randomization07.Non inferiority and equivalence
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• 14.Randomization08.Parallel
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• 14.Randomization09.Platform
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• 14.Randomization10.Basket and umbrella
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• 14.Randomization11.Master observation trial
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• 14.Randomization12.Randomization schedules
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• 14.Randomization13.Pragmatic
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• 15.Sensors.Pre requisites for sensors
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• 15.Sensors01.Smartwatch
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• 15.Sensors02.EKG
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• 15.Sensors03.Sound
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• 15.Sensors04.Hear rate variability
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• 17.Spatial analysis.Common packages for spatial analysis
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• 17.Spatial analysis.Pre requisites for spatial analysis
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• 17.Spatial analysis01.Geographic information systems
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• 17.Spatial analysis02.GIS dynamic maps
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• 17.Spatial analysis03.Spatio temporal analysis
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• 18.Time series.Pre requisites for time series
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• 18.Time series01.Association
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• 18.Time series02.Change point analysis
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• 18.Time series03.Forecast
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• 18.Time series04.Autoregression
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• 19.Visualization01.Standalone plots
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• 19.Visualization02.Dashboards
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• 200ks_Med_ResPaper_Abstracts
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• 2010 i2b2 VA
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• 2011 i2b2 VA
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• 2012 i2b2
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• 21.Reporting Guidelines01.EQUATOR checklist
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• 21.Reporting Guidelines02.PROBAST checklist
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• 21.Reporting Guidelines03.PROGRESSplus framework
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• 21.Reporting Guidelines04.PRISMA Equity_checklist
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• 4DN DP
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• AARP
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• AC MRI
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• ACAG
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• AccessClinicalData
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• ACRD
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• ACS
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• ADDEP
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• ADDI
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• ADI
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• ADKP
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• AHA
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• AHRF
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• AHRQ
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• Air Quality and Meteorological Information of Chile
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• ALFA
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• AllOfUs
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• AMDS
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• AMGA
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• AMP PD
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• ANA
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• APCDs
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• AphasiaBank
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• ARB
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• ARS
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• ARSA
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• ASCQ Me
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• AYA HOPE
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• Base de Datos de Facil Acceso del Censo 2017 de Chile
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• BCAC
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• BCBSNC
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• BCSC
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• BDC
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• Bengali_Medical_Dataset
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• BIDMC
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• BIFAP
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• BIL
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• BindingDB
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• BioASQ
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• BioBERT_QA_Model
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• BioLINCC
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• BioPortal
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• BioSystics AP
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• BioVU
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• BKAI IGH_NeoPolyp Small
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• BOD
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• BossDB
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• BRFSS
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• Broadband Deployment Data
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• BSO
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• BV BRC
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• CAHPS(R) Database
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• caNanoLab
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• CAPER
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• CART
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• Caserta
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• CASI
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• CCDI CCDC
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• CCDI MTP
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• CCHMC
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• CDE
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• CDI
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• CDS
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• CDW
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• CEDCD
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• CEGS GRID
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• Census Tract
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• censusIncarceration
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• CFDE
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• CHARLS
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• Chatbot
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• CHILDES
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• CHRR
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• CHSI
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• CI5
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• CIBMTR
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• CIL
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• CIMRD
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• CKD SS
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• ClinicalTrials
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• ClinVar
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• CMDKP
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• CMS claims data
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• CMS Cost Reports
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• CMS Hospital Compare
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• CMS–Physician Compare
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• ColonoscopicImagingDatabases
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• COMETS
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• Connect
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• Copernicus
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• CORD 19
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• CORD 19_corpus Mining
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• CoreNLP
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• COSM
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• COUGHVID 3
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• COVID 19 vaccinations
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• COVID 19_EA
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• COVID 19_Graphs
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• COVID 19_Translations
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• COVID 19_Tweets
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• COVID 19_Tweets_India
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• COVID 19_Xray
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• CP CHILD A
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• CP CHILD B
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• CPRD
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• CP‐CHILD B
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• CRE
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• CRISP
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• CRN
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• CRUK
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• CVC ClinicVideoDB
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• DARR
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• DARWIN
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• DASH
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• database_template
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• Databrary
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• Datasets through NBER
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• DAVID
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• DAWN
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• dbGaP
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• dbSNP
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• DCI
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• DEERS
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• Delphi Epidata API COVIDcast Epidata API
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