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

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

810
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
810
Nursing Clinical Information System01:27

Nursing Clinical Information System

884
Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
884
Data Collection II01:29

Data Collection II

8.7K
The nursing history captures and records the patient's health status, so that a care plan evolves to meet the patient's individual needs. The nursing health history is a part of the initial assessment. A comprehensive history covers all health dimensions and plays a significant role in the assessment process. A comprehensive history includes the patient's biographical information, reasons for seeking health care, expectations, present and past health history, medications, and...
8.7K
Data Validation01:03

Data Validation

5.5K
Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
Nursing assessment guides are generally based on holistic models rather than medical...
5.5K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

561
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
561

You might also read

Related Articles

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

Sort by
Same author

[Study on Standardization Methods of Multi-Source Heterogeneous Data from ICU Medical Devices Based on openEHR].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation·2026
Same author

LLM-DQR: Large language model-based automated generation of data quality rules for electronic health records.

Journal of biomedical informatics·2025
Same author

Learning from experts: A self-improving LLM framework for study population generation in clinical research.

International journal of medical informatics·2025
Same author

PSAT1 impairs ferroptosis and reduces immunotherapy efficacy via GPX4 hydroxylation.

Nature chemical biology·2025
Same author

Transforming Cancer Therapy: Unlocking the Potential of Targeting Vascular and Stromal Cells in the Tumor Microenvironment.

Cancer research·2025
Same author

Impact of Elevated Intraocular Pressure on Lamina Cribrosa Oxygenation: A Combined Experimental-Computational Study on Monkeys.

Ophthalmology science·2025
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles

Related Experiment Video

Updated: Sep 20, 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

16.0K

A Semi-Automatic Data Cleaning & Coding Tool for Chinese Clinical Data Standardization.

Yani Chen1, Qi Tian1, Hailing Cai1

  • 1College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang Province, China.

Studies in Health Technology and Informatics
|June 8, 2022
PubMed
Summary
This summary is machine-generated.

Standardizing Chinese clinical data with a new computer-aided tool improves usability. This process significantly enhances efficiency for tasks like diagnosis and drug coding.

Keywords:
Automatic Data ProcessingStandardization

More Related Videos

Author Spotlight: Exploring Sex-Specific Glial Signatures and Therapeutic Leads for Alzheimer's Disease
04:22

Author Spotlight: Exploring Sex-Specific Glial Signatures and Therapeutic Leads for Alzheimer's Disease

Published on: May 20, 2024

989
Author Spotlight: Exploring ShiDuGao's Multi-Target Approach in Anus Eczema Treatment
12:34

Author Spotlight: Exploring ShiDuGao's Multi-Target Approach in Anus Eczema Treatment

Published on: January 12, 2024

919

Related Experiment Videos

Last Updated: Sep 20, 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

16.0K
Author Spotlight: Exploring Sex-Specific Glial Signatures and Therapeutic Leads for Alzheimer's Disease
04:22

Author Spotlight: Exploring Sex-Specific Glial Signatures and Therapeutic Leads for Alzheimer's Disease

Published on: May 20, 2024

989
Author Spotlight: Exploring ShiDuGao's Multi-Target Approach in Anus Eczema Treatment
12:34

Author Spotlight: Exploring ShiDuGao's Multi-Target Approach in Anus Eczema Treatment

Published on: January 12, 2024

919

Area of Science:

  • Medical Informatics
  • Health Data Science
  • Clinical Data Management

Background:

  • Clinical data often lacks usefulness due to varied expression.
  • Manual coding of Chinese clinical data is complex and inefficient.
  • Computer-aided tools are needed to improve clinical data standardization.

Purpose of the Study:

  • To establish a universal data cleaning and coding process for Chinese clinical data standardization.
  • To develop a computer-aided tool to enhance the efficiency of clinical data standardization.
  • To assess the effectiveness of the developed process and tool.

Main Methods:

  • Developed a universal data cleaning and coding process.
  • Incorporated preprocessing, text similarity algorithms, and manual review.
  • Created a computer-aided tool to support the standardization process.

Main Results:

  • The established process and tool proved effective for standardizing diagnosis, drug, and examination data.
  • Semi-automatic data cleaning and coding reduced standardization time by 50%.
  • The system was successfully implemented in Beijing hospitals.

Conclusions:

  • The developed universal process and tool significantly improve human efficiency in clinical data standardization.
  • The semi-automatic approach offers a substantial time reduction for data standardization tasks.
  • The methodology is applicable to various clinical domains, promoting broader adoption.