Name
Affiliation
Papers
ROBERT M CRONIN
Vanderbilt Univ, Dept Med, Nashville, TN 37232 USA
24
Collaborators
Citations 
PageRank 
121
63
9.71
Referers 
Referees 
References 
297
616
168
Search Limit
100616
Title
Citations
PageRank
Year
Comparing medical history data derived from electronic health records and survey answers in the All of Us Research Program00.342022
Comparison Of Family Health History In Surveys Vs Electronic Health Record Data Mapped To The Observational Medical Outcomes Partnership Data Model In The All Of Us Research Program00.342021
Determinants of Medication Adherence in Sickle Cell Disease Using the World Health Organization Model.00.342019
Sickle Cell Disease Phenotype Algorithm Performance in Adult, Pediatric, and Transitional Care.00.342019
Quality Analysis of the All of Us Research Program Health Surveys.00.342019
Mining 100 million notes to find homelessness and adverse childhood experiences: 2 case studies of rare and severe social determinants of health in electronic health records.30.452018
Common Consumer Health-Related Needs in the Pediatric Hospital Setting: Lessons from an Engagement Consultation Service.00.342018
A technology-based patient and family engagement consult service for the pediatric hospital setting.10.362018
The Role of Information Technologies in Sickle Cell Disease Support Systems.00.342018
Patient and healthcare provider views on a patient-reported outcomes portal.10.372018
Technology use and preferences to support clinical practice guideline awareness and adherence in individuals with sickle cell disease.00.342018
Development of a Technology-Supported, Lay Peer-to-Peer Family Engagement Consultation Service in a Pediatric Hospital.00.342018
Classifying Patient Portal Messages Using Convolutional Neural Networks.20.382017
Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals.90.552017
Meeting Common Health-Related Needs Through a Pediatric Inpatient Engagement Consultation Service.00.342017
A comparison of rule-based and machine learning approaches for classifying patient portal messages.60.492017
Combining billing codes, clinical notes, and medications from electronic health records provides superior phenotyping performance.100.552016
Automated Classification of Consumer Health Information Needs in Patient Portal Messages.60.492015
National Veterans Health Administration inpatient risk stratification models for hospital-acquired acute kidney injury.30.472015
Evaluation of Diagnosis Codes, Clinical Notes, and Medications on Identifying Subjects with a Specific Disease Phenotype.00.342014
Research and applications: Assisted annotation of medical free text using RapTAT.00.342014
Development and evaluation of an ensemble resource linking medications to their indications.220.862013
Use and Evaluation of RapTAT-Assisted Annotation for Extraction of Acute Kidney Injury Concepts from Clinical Free Text.00.342013
Methods for Detection of Kidney Disease Risk Factors in Clinical Reports.00.342013