Клинические заметки

material ID: clinicalnotes

Related Papers

Automatic Mapping Clinical Notes to Medical Terminologies

Authors: nan

Publication: TIPSTER (2006)

DOI: nan

Automatic mapping of key concepts from clinical notes to a terminology is an im- portant task to achieve for extraction of the clinical information locked in clinical notes and patient …...

28739

Automated Proof Reading of Clinical Notes

Authors: nan

Publication: TIPSTER (2011)

DOI: nan

. Misspellings, abbreviations and acronyms are very popular in clinical notes and can be an obstacle to high quality information extraction and classification. In addition, another important part of narrative …...

18815

ThinkMiners: Disorder Recognition using Conditional Random Fields and Distributional Semantics

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

In 2014, SemEval organized multiple chal- lenges on natural language processing and information retrieval. One of the task was analysis of the clinical text. This challenge is further divided into …...

22715

Annotating and Detecting Medical Events in Clinical Notes

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractEarly detection and treatment of diseases that onset after a patient is admitted to a hospital, such as pneumonia, is critical to improving and reducing costs in healthcare. Previous studies …...

15171

Hitachi at SemEval-2017 Task 12: System for temporal information extraction from clinical notes

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractThis paper describes the system developed for the task of temporal information extraction from clinical narratives in the context of the 2017 Clinical TempEval challenge. Clinical TempEval 2017 addressed the …...

24314

Explainable Prediction of Medical Codes from Clinical Text

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

AbstractClinical notes are text documents that are created by clinicians for each patient encounter. They are typically accompanied by medical codes, which describe the diagnosis and treatment. Annotating these codes …...

20933

Using Clinical Notes with Time Series Data for ICU Management

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractMonitoring patients in ICU is a challenging and high-cost task. Hence, predicting the condition of patients during their ICU stay can help provide better acute care and plan the hospital’s …...

7626

Adapting Event Extractors to Medical Data: Bridging the Covariate Shift

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractWe tackle the task of adapting event extractors to new domains without labeled data, by aligning the marginal distributions of source and target domains. As a testbed, we create two …...

42558

Automatic ICD Coding via Interactive Shared Representation Networks with Self-distillation Mechanism

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Publication: TIPSTER (2021)

DOI: nan

AbstractThe ICD coding task aims at assigning codes of the International Classification of Diseases in clinical notes. Since manual coding is very laborious and prone to errors, many methods have …...

8179

A Whole-Person Function Dictionary for the Mobility, Self-Care and Domestic Life Domains: a Seedset Expansion Approach

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Publication: TIPSTER (2022)

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AbstractWhole-person functional limitations in the areas of mobility, self-care and domestic life affect a majority of individuals with disabilities. Detecting, recording and monitoring such limitations would benefit those individuals, as …...

15555

Leveraging Task Transferability to Meta-learning for Clinical Section Classification with Limited Data

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Publication: TIPSTER (2022)

DOI: nan

AbstractIdentifying sections is one of the critical components of understanding medical information from unstructured clinical notes and developing assistive technologies for clinical note-writing tasks. Most state-of-the-art text classification systems require …...

38918

Clinical Note Owns its Hierarchy: Multi-Level Hypergraph Neural Networks for Patient-Level Representation Learning

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Publication: TIPSTER (2023)

DOI: nan

AbstractLeveraging knowledge from electronic health records (EHRs) to predict a patient’s condition is essential to the effective delivery of appropriate care. Clinical notes of patient EHRs contain valuable information from …...

38564

Modelling Temporal Document Sequences for Clinical ICD Coding

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractPast studies on the ICD coding problem focus on predicting clinical codes primarily based on the discharge summary. This covers only a small fraction of the notes generated during each …...

42969

Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractMultitask deep learning has been applied to patient outcome prediction from text, taking clinical notes as input and training deep neural networks with a joint loss function of multiple tasks. …...

43041