Representation Learning for Electronic Health Records

09/19/2019
by   Wei-Hung Weng, et al.
0

Information in electronic health records (EHR), such as clinical narratives, examination reports, lab measurements, demographics, and other patient encounter entries, can be transformed into appropriate data representations that can be used for downstream clinical machine learning tasks using representation learning. Learning better representations is critical to improve the performance of downstream tasks. Due to the advances in machine learning, we now can learn better and meaningful representations from EHR through disentangling the underlying factors inside data and distilling large amounts of information and knowledge from heterogeneous EHR sources. In this chapter, we first introduce the background of learning representations and reasons why we need good EHR representations in machine learning for medicine and healthcare in Section 1. Next, we explain the commonly-used machine learning and evaluation methods for representation learning using a deep learning approach in Section 2. Following that, we review recent related studies of learning patient state representation from EHR for clinical machine learning tasks in Section 3. Finally, in Section 4 we discuss more techniques, studies, and challenges for learning natural language representations when free texts, such as clinical notes, examination reports, or biomedical literature are used. We also discuss challenges and opportunities in these rapidly growing research fields.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/01/2018

Opportunities in Machine Learning for Healthcare

Healthcare is a natural arena for the application of machine learning, e...
research
04/10/2023

Toward Cohort Intelligence: A Universal Cohort Representation Learning Framework for Electronic Health Record Analysis

Electronic Health Records (EHR) are generated from clinical routine care...
research
05/03/2021

Machine Learning Applications for Therapeutic Tasks with Genomics Data

Thanks to the increasing availability of genomics and other biomedical d...
research
04/12/2022

Deep Normed Embeddings for Patient Representation

We introduce a novel contrastive representation learning objective and a...
research
10/04/2019

Unsupervised Representation for EHR Signals and Codes as Patient Status Vector

Effective modeling of electronic health records presents many challenges...
research
02/12/2018

Embedding Complexity In the Data Representation Instead of In the Model: A Case Study Using Heterogeneous Medical Data

Electronic Health Records have become popular sources of data for second...
research
10/06/2020

Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review

Patient representation learning refers to learning a dense mathematical ...

Please sign up or login with your details

Forgot password? Click here to reset