Harvard Catalyst Profiles

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Ronilda C. Lacson, Ph.D., M.D.

Co-Author

This page shows the publications co-authored by Ronilda Lacson and Ivan Ip.
Connection Strength

1.714
  1. Classifying Safety Events Related to Diagnostic Imaging From a Safety Reporting System Using a Human Factors Framework. J Am Coll Radiol. 2019 Mar; 16(3):282-288.
    View in: PubMed
    Score: 0.204
  2. Integrity of clinical information in computerized order requisitions for diagnostic imaging. J Am Med Inform Assoc. 2018 12 01; 25(12):1651-1656.
    View in: PubMed
    Score: 0.203
  3. Medicare Imaging Demonstration: Assessing Attributes of Appropriate Use Criteria and Their Influence on Ordering Behavior. AJR Am J Roentgenol. 2017 May; 208(5):1051-1057.
    View in: PubMed
    Score: 0.180
  4. JOURNAL CLUB: Predictors of Provider Response to Clinical Decision Support: Lessons Learned From the Medicare Imaging Demonstration. AJR Am J Roentgenol. 2017 Feb; 208(2):351-357.
    View in: PubMed
    Score: 0.177
  5. Assessing Strength of Evidence of Appropriate Use Criteria for Diagnostic Imaging Examinations. J Am Med Inform Assoc. 2016 05; 23(3):649-53.
    View in: PubMed
    Score: 0.167
  6. Retrieval of radiology reports citing critical findings with disease-specific customization. Open Med Inform J. 2012; 6:28-35.
    View in: PubMed
    Score: 0.131
  7. Variation in Radiologists' Follow-Up Imaging Recommendations for Small Cystic Pancreatic Lesions. J Am Coll Radiol. 2021 10; 18(10):1405-1414.
    View in: PubMed
    Score: 0.061
  8. Radiologist Variation in the Rates of Follow-up Imaging Recommendations Made for Pulmonary Nodules. J Am Coll Radiol. 2021 07; 18(7):896-905.
    View in: PubMed
    Score: 0.059
  9. Comparing Tumor Characteristics and Rates of Breast Cancers Detected by Screening Digital Breast Tomosynthesis and Full-Field Digital Mammography. AJR Am J Roentgenol. 2020 03; 214(3):701-706.
    View in: PubMed
    Score: 0.054
  10. Fast Healthcare Interoperability Resources, Clinical Quality Language, and Systematized Nomenclature of Medicine-Clinical Terms in Representing Clinical Evidence Logic Statements for the Use of Imaging Procedures: Descriptive Study. JMIR Med Inform. 2019 May 13; 7(2):e13590.
    View in: PubMed
    Score: 0.052
  11. Variation in Follow-up Imaging Recommendations in Radiology Reports: Patient, Modality, and Radiologist Predictors. Radiology. 2019 06; 291(3):700-707.
    View in: PubMed
    Score: 0.052
  12. Assessing information sources to elucidate diagnostic process errors in radiologic imaging - a human factors framework. J Am Med Inform Assoc. 2018 11 01; 25(11):1507-1515.
    View in: PubMed
    Score: 0.051
  13. Patient, Radiologist, and Examination Characteristics Affecting Screening Mammography Recall Rates in a Large Academic Practice. J Am Coll Radiol. 2019 Apr; 16(4 Pt A):411-418.
    View in: PubMed
    Score: 0.050
  14. High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels. J Am Coll Radiol. 2018 Aug; 15(8):1133-1138.
    View in: PubMed
    Score: 0.049
  15. Characteristics of knowledge content in a curated online evidence library. J Am Med Inform Assoc. 2018 05 01; 25(5):507-514.
    View in: PubMed
    Score: 0.049
  16. Risk Stratification Model: Lower-Extremity Ultrasonography for Hospitalized Patients with Suspected Deep Vein Thrombosis. J Gen Intern Med. 2018 01; 33(1):21-25.
    View in: PubMed
    Score: 0.047
  17. Comparing Diagnostic Performance of Digital Breast Tomosynthesis and Full-Field Digital Mammography in a Hybrid Screening Environment. AJR Am J Roentgenol. 2017 Oct; 209(4):929-934.
    View in: PubMed
    Score: 0.046
  18. Evaluating Terminologies to Enable Imaging-Related Decision Rule Sharing. AMIA Annu Symp Proc. 2016; 2016:2082-2089.
    View in: PubMed
    Score: 0.045
  19. Gastrointestinal stromal tumor: optimizing the use of cross-sectional chest imaging during follow-up. Radiology. 2015 Feb; 274(2):395-404.
    View in: PubMed
    Score: 0.038
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.