Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

200
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
200
Hazard Ratio01:12

Hazard Ratio

293
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
293
Sensitivity, Specificity, and Predicted Value01:13

Sensitivity, Specificity, and Predicted Value

806
In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
806
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.1K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
18.1K
The Availability Heuristic01:08

The Availability Heuristic

6.6K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
6.6K
Methods of Documentation II: POMR01:26

Methods of Documentation II: POMR

1.1K
The Problem-Oriented Medical Record (POMR) revolutionized medical record-keeping by introducing a systematic approach focusing on the patient's problems rather than merely listing symptoms. Dr. Lawrence Weed's introduction of this method in the 1960s marked a significant advancement in medical documentation. The POMR framework consists of four key components: the database, problem list, plan of care, and progress notes.
1.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Artificial intelligence methods to detect heart failure with preserved ejection fraction within electronic health records: an equitable disease detection model.

European heart journal. Digital health·2026
Same author

CSAI: Conditional Self-Attention Imputation for Healthcare Time-Series.

IEEE journal of biomedical and health informatics·2025
Same author

Evaluating the Clinical Effectiveness and Patient Experience of a Large Language Model-Based Digital Tool for Home-Based Blood Pressure Management: Mixed Methods Study.

JMIR mHealth and uHealth·2025
Same author

Exploring biases related to the use of large language models in a multilingual depression corpus.

Scientific reports·2025
Same author

A Dual In-Person and Remote Assessment Approach to Developing Digital End Points Relevant to Autism and Co-Occurring Conditions: Protocol for a Multisite Observational Study.

JMIR research protocols·2025
Same author

Collection and Analysis of Repeated Speech Samples: Methodological Framework and Example Protocol.

JMIR research protocols·2025
Same journal

Causal intervention validation of gene regulatory signals in scGPT.

Journal of biomedical informatics·2026
Same journal

CoAff-DTI: Fine-grained drug-target interaction prediction using pre-trained language models and affinity-guided mechanisms.

Journal of biomedical informatics·2026
Same journal

Evaluation of temporal preservation in synthetic longitudinal patient data.

Journal of biomedical informatics·2026
Same journal

ARKE: An ontology-driven framework for automated mapping of local radiology procedure terms to the LOINC-RadLex playbook using large language model.

Journal of biomedical informatics·2026
Same journal

A validation-driven training controller for cross-lingual biomedical NER via reinforcement learning-based adaptive loss weighting.

Journal of biomedical informatics·2026
Same journal

ASP-HR: An Adaptive Spatial Perception and Hierarchical Reasoning mechanism for document-level biomedical relation extraction.

Journal of biomedical informatics·2026
See all related articles

Related Experiment Video

Updated: Oct 15, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.1K

Estimating redundancy in clinical text.

Thomas Searle1, Zina Ibrahim1, James Teo2

  • 1Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Journal of Biomedical Informatics
|October 25, 2021
PubMed
Summary
This summary is machine-generated.

Electronic Health Records (EHR) contain significant text redundancy due to note duplication. Quantifying this redundancy is crucial for improving clinical data accuracy and evaluating new healthcare innovations.

Keywords:
Deep transfer learning for language modelling of clinical textNatural language processing methods to estimate redundancy of clinical text

More Related Videos

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

4.8K
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

8.9K

Related Experiment Videos

Last Updated: Oct 15, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

16.1K
TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
09:00

TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients

Published on: April 13, 2021

4.8K
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
09:20

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications

Published on: February 23, 2019

8.9K

Area of Science:

  • Medical Informatics
  • Natural Language Processing
  • Health Data Science

Background:

  • Current Electronic Health Records (EHR) practices involve duplicating existing notes to create new entries, leading to significant text redundancy.
  • This data duplication can propagate errors, introduce inconsistencies, and result in misreporting of patient care.
  • Quantifying information redundancy in clinical narratives is essential for assessing the impact of innovations in healthcare data management.

Purpose of the Study:

  • To quantitatively examine information redundancy within EHR notes.
  • To present and evaluate two novel methods for measuring redundancy in clinical text.
  • To assess the efficiency and redundancy levels of clinical text compared to open-domain corpora.

Main Methods:

  • Utilized Transformer-based language models trained on large clinical datasets (US ICU and UK hospital data) for an information-theoretic approach.
  • Compared the information-theoretic efficiency of clinical text against open-domain corpora.
  • Employed automated summarization metrics (ROUGE and BERTScore) to evaluate lexicosyntactic and semantic redundancy in successive EHR note pairs.

Main Results:

  • Clinical text was found to be 1.5x to 3x less information-theoretically efficient than open-domain corpora.
  • Automated summarization metrics indicated significant lexicosyntactic and semantic redundancy in successive EHR notes, averaging between 43% and 65%.

Conclusions:

  • EHR notes exhibit substantial information redundancy, impacting data integrity and efficiency.
  • The developed methods provide quantitative measures for assessing redundancy in clinical text.
  • Findings highlight the need for strategies to mitigate redundancy and improve the quality of clinical data in EHR systems.