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Web-based Real-Time Case Finding for the Population Health Management of Patients With Diabetes Mellitus: A Prospective Validation of the Natural Language Processing–Based Algorithm With Statewide Electronic Medical Records

Web-based Real-Time Case Finding for the Population Health Management of Patients With Diabetes Mellitus: A Prospective Validation of the Natural Language Processing–Based Algorithm With Statewide Electronic Medical Records

As a result, the inference of DM diagnosis for a codified note was only dependent on the ICD code noted in the structured data, whereas for uncodified notes we trained a random forest model [33,38] to obtain T(f) (Figure 3 (g)), where tn was the n th decision tree in the random forest. At the perspective of hierarchical tree, the model could be considered as a combination of a predetermined tree-based model and a random forest-based model.

Le Bruce Zheng, Yue Wang, Shiying Hao, Andrew Y Shin, Bo Jin, Anh D Ngo, Medina S Jackson-Browne, Daniel J Feller, Tianyun Fu, Karena Zhang, Xin Zhou, Chunqing Zhu, Dorothy Dai, Yunxian Yu, Gang Zheng, Yu-Ming Li, Doff B McElhinney, Devore S Culver, Shaun T Alfreds, Frank Stearns, Karl G Sylvester, Eric Widen, Xuefeng Bruce Ling

JMIR Med Inform 2016;4(4):e37