Elscint was an Israeli technology company that developed, manufactured and sold medical imaging solutions, including: nuclear medicine, computed tomography magnetic resonance imaging and X-ray scanners. Elscint's shares traded on the NASDAQ as well as on the Tel Aviv Stock Exchange. At its height, Elscint was a world leader in the development of medical…
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Elscint topic overview
The analysis highlights History, Products, Technology and Companies as prominent areas in the source structure around Elscint.
Related topics
25
Source areas
2
Connected nodes
27
Extracted relationships
59
Concept neighborhoods
17
Bridge connections
27
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 · 13 topics
History · 12 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.
Founded
1969; 57 years ago (1969)
Industry
Medical imaging
Headquarters
Haifa, Israel
Defunct
2005
Fate
sold
Founder
Avraham Suhami
Explore all related topics Closing gaps
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 Elscint 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 Elscint shows recurring relationship patterns in the source. For example, Elscint → Avraham Suhami, CEO, Chairman, Dan Tolkovsky, Discount Investment Corporation, Dr, El, El Al, Elron, Elscint's, Israel Institute, Later, Nuclear Medicine, Scint, Suhami, Technion, Technology, The, US, Uzia Galil Another extracted example is Elscint → After, By, CT, During, Elbit Computers, Elbit Computers Ltd, Elbit Medical Imaging, Elron, Elscint CT Twin, GE, GE Healthcare, In, Philips Medical Systems, Picker, Siemens, The VolumeX, This, Twin, VolumeX. Use these groups to spot repeated connection types before inspecting the individual relationships.
Elscint
Top relations
related to 1969–1974: Early years· 21
Elscint → Avraham Suhami, CEO, Chairman, Dan Tolkovsky, Discount Investment Corporation, Dr, El, El Al, Elron, Elscint's, Israel Institute, Later, Nuclear Medicine, Scint, Suhami, Technion, Technology, The, US, Uzia Galil
related to Breakup· 19
Elscint → After, By, CT, During, Elbit Computers, Elbit Computers Ltd, Elbit Medical Imaging, Elron, Elscint CT Twin, GE, GE Healthcare, In, Philips Medical Systems, Picker, Siemens, The VolumeX, This, Twin, VolumeX
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 59 structured relationships around Elscint. Examples in this analysis include Elscint → Defunct → 2005 and Elscint → Fate → sold. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Elscint
Defunct
2005
1.00
infobox
Elscint
Fate
sold
1.00
infobox
Elscint
Founded
1969; 57 years ago (1969)
1.00
infobox
Elscint
Founder
Avraham Suhami
1.00
infobox
Elscint
Headquarters
Haifa, Israel
1.00
infobox
Elscint
Industry
Medical imaging
1.00
infobox
Elscint
Net income
US$ 8,100,000 (1996)
1.00
infobox
Elscint
Number of employees
2000 (1996)
1.00
infobox
Elscint
Parent
Elron
1.00
infobox
Elscint
Products
Computerized tomography, Magnetic resonance imaging, Ultrasound, X-ray scanners
1.00
infobox
Elscint
Revenue
US$ 311,000,000 (1996)
1.00
infobox
Elscint
Type
Public
1.00
infobox
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 Elscint bring nearby vocabulary together. In this analysis, examples include Imaging, Medical and First. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Elscint
Imaging
Medical
First
Products
Scanners
Subsidiary
Time
World
Elbit
X-ray
Suhami
Tomography
elscint
Imaging
Medical
First
Products
Scanners
Subsidiary
Time
World
Elbit
X-ray
Suhami
Tomography
medical imaging
Medical
Elbit
Sold
Activities
Nuclear
Product
First
Magnetic
Resonance
Systems
X-ray
Products
magnetic resonance imaging
Resonance
Medical
X-ray
Scanners
Tomography
Elbit
Sold
Nuclear
Product
Israel
Systems
Technology
philips medical systems
Elbit
Sold
Activities
Nuclear
Magnetic
Resonance
Systems
X-ray
Products
Scanners
Tomography
Elron
elron electronic industries
Israel
Suhami
Elbit
Subsidiary
Nuclear
Sold
Imaging
Medical
Elscint
Time
Israeli
Magnetic
elbit medical imaging
Medical
Elbit
Imaging
Sold
Elron
Activities
Nuclear
Product
Subsidiary
Elscint
First
Magnetic
holding company
Imaging
Medical
Elbit
Sold
Developed
Israeli
Time
Exchange
Elron
Nuclear
Million
Elscint
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 Elscint, one of the stronger structural bridges in this analysis connects Elscint 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.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Elscint
Nodes28
Edges27
Triples59
Avg. degree1.93
Density0.071429
Components1
Source & methodology
TTTA analyzes the structure around Elscint to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Products, Technology & Companies, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
