Enhancing Comparative Effectiveness Research With Automated Pediatric Pneumonia Detection in a Multi-Institutional Clinical Repository: A PHIS+ Pilot Study

Journals

1. Pu J, Leader J, Bandos A, Ke S, Wang J, Shi J, Du P, Guo Y, Wenzel S, Fuhrman C, Wilson D, Sciurba F, Jin C. Automated quantification of COVID-19 severity and progression using chest CT images. European Radiology 2021;31(1):436 View
2. Gabriel R, Kuo T, McAuley J, Hsu C. Identifying and characterizing highly similar notes in big clinical note datasets. Journal of Biomedical Informatics 2018;82:63 View
3. Shore B, Hall M, Matheney T, Snyder B, Trenor C, Berry J. Incidence of Pediatric Venous Thromboembolism After Elective Spine and Lower-Extremity Surgery in Children With Neuromuscular Complex Chronic Conditions: Do we Need Prophylaxis?. Journal of Pediatric Orthopaedics 2020;40(5):e375 View
4. Spasic I, Nenadic G. Clinical Text Data in Machine Learning: Systematic Review. JMIR Medical Informatics 2020;8(3):e17984 View
5. Horvat C, Ogoe H, Kantawala S, Au A, Fink E, Yablonsky E, Kochanek P, Suresh S, Clark R. Development and Performance of Electronic Pediatric Risk of Mortality and Pediatric Logistic Organ Dysfunction-2 Automated Acuity Scores*. Pediatric Critical Care Medicine 2019;20(8):e372 View
6. Caballé-Cervigón N, Castillo-Sequera J, Gómez-Pulido J, Gómez-Pulido J, Polo-Luque M. Machine Learning Applied to Diagnosis of Human Diseases: A Systematic Review. Applied Sciences 2020;10(15):5135 View
7. Casey A, Davidson E, Poon M, Dong H, Duma D, Grivas A, Grover C, Suárez-Paniagua V, Tobin R, Whiteley W, Wu H, Alex B. A systematic review of natural language processing applied to radiology reports. BMC Medical Informatics and Decision Making 2021;21(1) View
8. Rixe N, Frisch A, Wang Z, Martin J, Suresh S, Florin T, Ramgopal S. The development of a novel natural language processing tool to identify pediatric chest radiograph reports with pneumonia. Frontiers in Digital Health 2023;5 View
9. Kiser A, Eilbeck K, Ferraro J, Skarda D, Samore M, Bucher B. Standard Vocabularies to Improve Machine Learning Model Transferability With Electronic Health Record Data: Retrospective Cohort Study Using Health Care–Associated Infection. JMIR Medical Informatics 2022;10(8):e39057 View
10. Chapman A, Peterson K, Rutter E, Nevers M, Zhang M, Ying J, Jones M, Classen D, Jones B. Development and evaluation of an interoperable natural language processing system for identifying pneumonia across clinical settings of care and institutions. JAMIA Open 2022;5(4) View
11. Linna N, Kahn C. Applications of natural language processing in radiology: A systematic review. International Journal of Medical Informatics 2022;163:104779 View
12. Ramgopal S, Kapes J, Alpern E, Carroll M, Heffernan M, Simon N, Florin T, Macy M. Perceptions of Artificial Intelligence-Assisted Care for Children With a Respiratory Complaint. Hospital Pediatrics 2023;13(9):802 View
13. Zavala-Díaz J, Olivares-Rojas J, Gutiérrez-Gnecchi J, Téllez-Anguiano A, Alcaraz-Chávez J, Reyes-Archundia E. Clinical notes classification system for automated identification of diabetic patients: Hybrid approach integrating rules, information extraction and machine learning. Journal of Intelligent & Fuzzy Systems 2024:1 View