ArticleBMC medical informatics and decision making2015
Care episode retrieval: distributional semantic models for information retrieval in the clinical domain.
Article in BMC medical informatics and decision making, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Clinical Information Retrieval: A Literature Review.Journal of healthcare informatics research · 2024Article
- Deep learning in clinical natural language processing: a methodical review.Journal of the American Medical Informatics Association : JAMIA · 2020Review
- Feature extraction for phenotyping from semantic and knowledge resources.Journal of biomedical informatics · 2019Article
- EHR phenotyping via jointly embedding medical concepts and words into a unified vector space.BMC medical informatics and decision making · 2018Article
- CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital.BMC medical informatics and decision making · 2018Article
- Effective Identification of Similar Patients Through Sequential Matching over ICD Code Embedding.Journal of medical systems · 2018Article
- Clinical Natural Language Processing in languages other than English: opportunities and challenges.Journal of biomedical semantics · 2018Review
- Joint Learning of Representations of Medical Concepts and Words from EHR Data.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2017Article
- A Part-Of-Speech term weighting scheme for biomedical information retrieval.Journal of biomedical informatics · 2016Article
- Text Mining the History of Medicine.PloS one · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients' health related information is stored in electronic health records (EHRs) by health service providers. These records include sequential documentation of care episodes in the form of clinical notes. EHRs are used throughout the health care sector by professionals, administrators and patients, primarily for clinical purposes, but also for secondary purposes such as decision support and research. The vast amounts of information in EHR systems complicate information management and increase the risk of information overload. Therefore, clinicians and researchers need new tools to manage the information stored in the EHRs. A common use case is, given a--possibly unfinished--care episode, to retrieve the most similar care episodes among the records. This paper presents several methods for information retrieval, focusing on care episode retrieval, based on textual similarity, where similarity is measured through domain-specific modelling of the distributional semantics of words. Models include variants of random indexing and the semantic neural network model word2vec. Two novel methods are introduced that utilize the ICD-10 codes attached to care episodes to better induce domain-specificity in the semantic model. We report on experimental evaluation of care episode retrieval that circumvents the lack of human judgements regarding episode relevance. Results suggest that several of the methods proposed outperform a state-of-the art search engine (Lucene) on the retrieval task.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.