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International Classification of Diseases: History, Versions & Overview
The International Classification of Diseases (ICD) is the globally authoritative medical classification and terminology used in epidemiology, health management, clinical diagnosis, and health information management, resource allocation, clinican recording, decision support and health financing. It exists currently in its eleventh revision ICD-11 and it…
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International Classification of Diseases topic overview
The analysis highlights History, Versions and Overview as prominent areas in the source structure around International Classification of Diseases.
Related topics
62
Source areas
6
Connected nodes
68
Extracted relationships
70
Concept neighborhoods
36
Bridge connections
68
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Overview · 37 topics
Versions · 11 topics
Usage in the United States · 6 topics
Early history · 5 topics
Mental health conditions · 2 topics
Usage in the European Union · 1 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Suggested research paths
A focused starting point derived from the topic graph, ranked independently of the source article order.
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How International Classification of Diseases connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around International Classification of Diseases shows recurring relationship patterns in the source. For example, International Classification of Diseases → Adapted, April, Clinical Modification, Diseases, Eighth Revision, Health, Hospital Records, However, Human Services, ICD, ICD-10, ICD-10-CM, ICD-10-PCS, ICD-7, ICD-9, ICD-9-CM, ICDA, ICDA-8, In, Indexing Another extracted example is International Classification of Diseases → As, Diseases, Following, For, Foundation, Foundation Component, From, ICD, ICD-10, ICD-11, ICD-11 MMS, ICD-O, International Classification, It, June, May, MMS, Morbidity Statistics, Mortality, The. Use these groups to spot repeated connection types before inspecting the individual relationships.
International Classification of Diseases
Top relations
related to Usage in the United States· 38
International Classification of Diseases → Adapted, April, Clinical Modification, Diseases, Eighth Revision, Health, Hospital Records, However, Human Services, ICD, ICD-10, ICD-10-CM, ICD-10-PCS, ICD-7, ICD-9, ICD-9-CM, ICDA, ICDA-8, In, Indexing
related to ICD-11· 22
International Classification of Diseases → As, Diseases, Following, For, Foundation, Foundation Component, From, ICD, ICD-10, ICD-11, ICD-11 MMS, ICD-O, International Classification, It, June, May, MMS, Morbidity Statistics, Mortality, The
related to ICD-7· 10
International Classification of Diseases → Diseases, February, Health Statistics, In, International Classification, Paris, Seventh Revision, The International Conference, WHO, WHO Expert Committee
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
International Classification of Diseases relationships Subject–Predicate–Object triples
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 70 structured relationships around International Classification of Diseases. Examples in this analysis include International Classification of Diseases → related to ICD-11 → The and International Classification of Diseases → related to ICD-11 → International Classification. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
International Classification of Diseases
related to ICD-11
The
0.60
section
International Classification of Diseases
related to ICD-11
International Classification
0.60
section
International Classification of Diseases
related to ICD-11
Diseases
0.60
section
International Classification of Diseases
related to ICD-11
ICD-11
0.60
section
International Classification of Diseases
related to ICD-11
ICD-10
0.60
section
International Classification of Diseases
related to ICD-11
It
0.60
section
International Classification of Diseases
related to ICD-11
Following
0.60
section
International Classification of Diseases
related to ICD-11
May
0.60
section
International Classification of Diseases
related to ICD-11
June
0.60
section
International Classification of Diseases
related to ICD-11
WHO
0.60
section
International Classification of Diseases
related to ICD-11
World Health Assembly
0.60
section
International Classification of Diseases
related to ICD-11
For
0.60
section
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around International Classification of Diseases bring nearby vocabulary together. In this analysis, examples include International, Diseases and Health. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
International Classification of Diseases
International
Diseases
Health
Icd
Statistical
Published
Causes
National
Public
Revision
United
States
international classification of diseases
International
Diseases
Health
Icd
Revision
Statistical
Published
Used
Causes
National
Public
United
a "family" of international classifications
Health
Statistical
Public
Published
Causes
National
Revision
United
Disorders
States
Mental
Us
health management
International
Icd
Public
United
Published
World
Us
Clinical
Care
States
Statistics
National
health information management
International
Icd
Public
United
Published
World
Us
Clinical
Care
States
Statistics
National
world health organization
International
Icd
Public
United
Health
Published
World
Us
Clinical
Care
States
Statistics
united nations system
States
Public
Diagnostic
Us
Procedures
Icd-10-cm
Published
Statistics
Codes
Icd-9-cm
Used
World
health data
Icd-9
International
Icd
Public
United
Published
World
Us
Clinical
Morbidity
Care
States
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For International Classification of Diseases, one of the stronger structural bridges in this analysis connects International Classification of Diseases with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Min side: 3
International Classification of Diseases — Overview· splits 31 ⟂ 38International Classification of Diseases — Versions· splits 57 ⟂ 12International Classification of Diseases — Usage in the United States· splits 62 ⟂ 7International Classification of Diseases — Early history· splits 63 ⟂ 6International Classification of Diseases — Mental health conditions· splits 66 ⟂ 3
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
International Classification of Diseases
Nodes69
Edges68
Triples70
Avg. degree1.97
Density0.028986
Components1
Source & methodology
TTTA analyzes the structure around International Classification of Diseases to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Versions & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
