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PEDRO J CARABALLO
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Name
Affiliation
Papers
PEDRO J CARABALLO
Mayo Clin, Div Gen Internal Med, Rochester, MN 55905 USA
19
Collaborators
Citations
PageRank
116
29
7.59
Referers
Referees
References
151
131
22
Search Limit
100
151
Publications (19 rows)
Collaborators (100 rows)
Referers (100 rows)
Referees (100 rows)
Title
Citations
PageRank
Year
A Computational Method for Learning Disease Trajectories From Partially Observable EHR Data
0
0.34
2021
Genomic considerations for FHIR®; eMERGE implementation lessons
0
0.34
2021
Predicting diabetes clinical outcomes using longitudinal risk factor trajectories.
0
0.34
2020
Integrating pharmacogenomics into the electronic health record by implementing genomic indicators.
0
0.34
2020
Pharmacogenomic clinical decision support design and multi-site process outcomes analysis in the eMERGE Network.
1
0.40
2019
Evaluating the Impact of Data Representation on EHR-Based Analytic Tasks.
0
0.34
2019
Towards more Accessible Precision Medicine: Building a more Transferable Machine Learning Model to Support Prognostic Decisions for Micro- and Macrovascular Complications of Type 2 Diabetes Mellitus.
0
0.34
2019
Frequent Causal Pattern Mining: A Computationally Efficient Framework For Estimating Bias-Corrected Effects
0
0.34
2019
Impact of the Performance Gap Between Interactive Alerts and Quality Metrics.
0
0.34
2019
Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.
2
0.41
2018
Empowering genomic medicine by establishing critical sequencing result data flows: the eMERGE example.
0
0.34
2018
Technical Challenges and Opportunities when Implementing Pharmacogenomics Decision Support Integrated in the Electronic Health Record.
0
0.34
2017
Providers' Response to Clinical Decision Support for QT Prolonging Drugs.
0
0.34
2017
Estimating Disease Onset Time by Modeling Lab Result Trajectories via Bayes Networks
0
0.34
2017
Type 2 Diabetes Mellitus Trajectories and Associated Risks.
4
0.42
2016
Survival Association Rule Mining Towards Type 2 Diabetes Risk Assessment.
5
0.43
2013
Quantifying the Effect of Statin Use in Pre-Diabetic Phenotypes Discovered Through Association Rule Mining.
1
0.34
2013
Clinical Burden and Risk of Alert Fatigue Associated with Detection and Documentation of Prolonged QT Interval Using an Expert Rule System.
0
0.34
2012
Impact of data fragmentation across healthcare centers on the accuracy of a high-throughput clinical phenotyping algorithm for specifying subjects with type 2 diabetes mellitus.
16
1.19
2012
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