Article

Optimizing Word Embeddings for Patient Portal Message Datasets with a Small Number of Samples

2024-05-15

Abstract excerpt

<title>Abstract</title> <p><bold>Background</bold> Patient portal messages often relate to specific clinical phenomena (e.g., patients undergoing treatment for breast cancer) and, as a result, have received increasing attention in biomedical research. These messages require natural language processing and, while word embedding models, such as word2vec, have the potential to extract meaningful signals from text, t...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: c06e4b8e-e851-598c-b3e3-240958cced65
DOI: 10.21203/rs.3.rs-4350387/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Optimizing Word Embeddings for Patient Portal Message Datasets with a Small Number of SamplesDOI 10.21203/rs.3.rs-4350387/v1Read

A Scalable Framework for Benchmarking Embedding Models for Semantic Medical TasksSemantic proximity Read

Text mining-based word representations for biomedical data analysis and machine learning tasksSemantic proximity Read

Phe2vec: Automated Disease Phenotyping based on Unsupervised Embeddings from Electronic Health RecordsSemantic proximity Read

An Intrinsic and Extrinsic Evaluation of Learned COVID-19 Concepts using Open-Source Word Embedding SourcesSemantic proximity Read

A Comparison of Representation Learning Methods for Medical Concepts in MIMIC-IVSemantic proximity Read

Language-model-based patient embedding using electronic health records facilitates phenotyping, disease forecasting, and progression analysisSemantic proximity Read

Predicting Rectal Cancer Patient Survival with Dutch Radiology Reports using Natural Language Processing (NLP): The Role of Pretrained Language ModelsSemantic proximity Read

CPP2Vec: a Representation Learning Approach for Cell-Penetrating Peptides PredictionSemantic proximity Read

Comparing natural language processing representations of disease sequences for prediction in the electronic healthcare recordSemantic proximity Read

Clinical Note Comparison and Data Retrieval Via Embedding Vectors: Model Selection, Metrics, and ConvergenceSemantic proximity Read

GenAI Exceeds Clinical Experts in Predicting Acute Kidney Injury following Paediatric Cardiopulmonary Bypass<sup>2</sup>Semantic proximity Read

Towards end-to-end disease prediction from raw metagenomic dataSemantic proximity Read