Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Classification of Illness

Classification of Illness

The meaning of illness is individualized to each person who experiences an alteration in health. In contrast, disease is a medical term indicating a pathological change in the structure and function of the body or mind. It is a condition that has specific symptoms and boundaries.
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...

You might also read

Related Articles

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

Sort by

Same author

Ischemic Postconditioning in Patients With Acute Stroke With Successful Recanalization After Endovascular Therapy: A Pilot Randomized Controlled Trial.

Stroke·2026

Same author

Antimicrobial resistance and plasmidome of carbapenemase-resistant Klebsiella pneumoniae causing bloodstream infections between 2014 and 2024.

BMC microbiology·2026

Same author

Editorial: Brain cytoprotection for reperfusion injury after acute ischemic stroke.

Frontiers in neurology·2026

Same author

Clinical outcomes of tebentafusp in metastatic uveal melanoma: a systematic review and single-arm meta-analysis.

Frontiers in medicine·2026

Same author

Preoperative prediction of lymphovascular and perineural invasion in locally advanced gastric cancer via CT habitat analysis and deep learning: A dual-center study.

European journal of radiology·2026

Same author

PuMYB40 and PuWRKY75 synergistically enhance phosphate uptake and organic phosphorus hydrolysis under phosphate deficiency in poplar.

Plant physiology·2026

Search research articles

Related Experiment Video

Updated: Dec 15, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

A benchmark dataset and case study for Chinese medical question intent classification.

Nan Chen¹, Xiangdong Su², Tongyang Liu¹

¹Inner Mongolia Key Laboratory of Mongolian Information Processing Technology, College of Computer Science, Inner Mongolia Univeristy, University West Road, Hohhot, China.

BMC Medical Informatics and Decision Making

|July 11, 2020

Summary

Researchers created the Chinese Medical Intent Dataset (CMID) for training AI models to understand user questions in medical question answering systems. Fast Text and TextCNN models showed the best performance in classifying intents.

Keywords:

Dataset Intent classification Name entity recognition Word segmentation

More Related Videos

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

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

Published on: September 20, 2018

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Related Experiment Videos

Last Updated: Dec 15, 2025

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Objectification of Tongue Diagnosis in Traditional Medicine, Data Analysis, and Study Application

Published on: April 14, 2023

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

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

Published on: September 20, 2018

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

Area of Science:

Natural Language Processing
Artificial Intelligence
Medical Informatics

Background:

Accurate understanding of user intent is crucial for medical question-answering (QA) systems.
Supervised deep learning approaches require high-quality datasets for medical intent classification.
Existing datasets are insufficient for Chinese medical intent classification.

Purpose of the Study:

To construct a comprehensive Chinese medical intent dataset (CMID).
To evaluate the performance of different intent classification models on this dataset.
To facilitate the development of advanced medical QA systems for Chinese users.

Main Methods:

Constructed CMID using 12,000 questions from Chinese medical QA websites.
Developed an intent annotation standard with medical experts, including 4 types and 36 subtypes.
Utilized crowdsourcing for intent annotation and employed Jieba and Lattice-LSTM for word segmentation and named entity recognition.

Main Results:

The CMID dataset is available in JSON format, including intent labels, word segmentation, and named entity information.
Comparative analysis of four deep learning models (Fast Text, TextCNN, TextRNN, TextGCN) was performed.
Fast Text and TextCNN achieved the highest accuracy for broad and specific intent classification, respectively.

Conclusions:

The developed CMID is a valuable resource for Chinese medical intent classification research.
The study provides insights into the effectiveness of different models for this task.
CMID can advance the development of intelligent medical QA systems and related applications.