LATTE: Label-efficient Incident Phenotyping from Longitudinal Electronic Health Records

1 code implementation • 19 May 2023 • Jun Wen, Jue Hou, Clara-Lea Bonzel, Yihan Zhao, Victor M. Castro, Vivian S. Gainer, Dana Weisenfeld, Tianrun Cai, Yuk-Lam Ho, Vidul A. Panickan, Lauren Costa, Chuan Hong, J. Michael Gaziano, Katherine P. Liao, Junwei Lu, Kelly Cho, Tianxi Cai

We propose a LAbel-efficienT incidenT phEnotyping (LATTE) algorithm to accurately annotate the timing of clinical events from longitudinal EHR data.

Representation Learning Unsupervised Pre-training