Amplifying Domain Expertise in Clinical Data Pipelines

Journals

1. Kerrigan D, Hullman J, Bertini E. A Survey of Domain Knowledge Elicitation in Applied Machine Learning. Multimodal Technologies and Interaction 2021;5(12):73 View
2. Oei R, Hsu W, Lee M, Tan N. Using similar patients to predict complication in patients with diabetes, hypertension, and lipid disorder: a domain knowledge-infused convolutional neural network approach. Journal of the American Medical Informatics Association 2023;30(2):273 View
3. Van Laere S, Muylle K, Dupont A, Cornu P. Machine Learning Techniques Outperform Conventional Statistical Methods in the Prediction of High Risk QTc Prolongation Related to a Drug-Drug Interaction. Journal of Medical Systems 2022;46(12) View
4. Pillai M, Griffin A, Kronk C, McCall T. Toward Community-Based Natural Language Processing (CBNLP): Cocreating With Communities. Journal of Medical Internet Research 2023;25:e48498 View
5. Rahman P, Ye C, Mittendorf K, Lenoue-Newton M, Micheel C, Wolber J, Osterman T, Fabbri D. Accelerated curation of checkpoint inhibitor-induced colitis cases from electronic health records. JAMIA Open 2023;6(1) View
6. Lim J, Kim S, Park J, Kim C, Choi J, Chang J, Kim S, Park I, Ha B, Jo I, Byeon H, Park K, Kim H, Jung S, Heo J. Systematic construction of composite radiation therapy dataset using automated data pipeline for prognosis prediction. International Journal of Medical Informatics 2025;195:105712 View

Books/Policy Documents

1. Janzen S, Stein H. Advances in Conceptual Modeling. View