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Computational Phenotyping

Computational Phenotyping is the process of transforming the noisy, massive Electronic Health Record (EHR) data into meaningful medical concepts that can be used to predict the risk of disease for an individual, or the response to drug therapy.

Source: Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis

Papers

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Showing 11–18 of 18 papers

TitleStatusHype
Unsupervised EHR-based Phenotyping via Matrix and Tensor Decompositions—0
Using Clinical Narratives and Structured Data to Identify Distant Recurrences in Breast Cancer—0
Communication Efficient Generalized Tensor Factorization for Decentralized Healthcare Networks—0
Distilling Knowledge from Deep Networks with Applications to Healthcare Domain—0
Federated Tensor Factorization for Computational Phenotyping—0
Implementing a Portable Clinical NLP System with a Common Data Model - a Lisp Perspective—0
Natural Language Processing for EHR-Based Computational Phenotyping—0
PHEONA: An Evaluation Framework for Large Language Model-based Approaches to Computational Phenotyping—0
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