Submit Search
Upload
Mining biomedical texts
•
Download as PPT, PDF
•
1 like
•
428 views
Lars Juhl Jensen
Follow
Technology
Report
Share
Report
Share
1 of 92
Download now
Recommended
Mining literature and medical records
Mining literature and medical records
Lars Juhl Jensen
Networks of proteins and diseases
Networks of proteins and diseases
Lars Juhl Jensen
Biomedical text mining
Biomedical text mining
Lars Juhl Jensen
Data and Text Mining
Data and Text Mining
Lars Juhl Jensen
Biomedical text mining and network analysis
Biomedical text mining and network analysis
Lars Juhl Jensen
Mining text and data on chemicals
Mining text and data on chemicals
Lars Juhl Jensen
Disease Systems Biology
Disease Systems Biology
Lars Juhl Jensen
Large-scale integration of data and text
Large-scale integration of data and text
Lars Juhl Jensen
Recommended
Mining literature and medical records
Mining literature and medical records
Lars Juhl Jensen
Networks of proteins and diseases
Networks of proteins and diseases
Lars Juhl Jensen
Biomedical text mining
Biomedical text mining
Lars Juhl Jensen
Data and Text Mining
Data and Text Mining
Lars Juhl Jensen
Biomedical text mining and network analysis
Biomedical text mining and network analysis
Lars Juhl Jensen
Mining text and data on chemicals
Mining text and data on chemicals
Lars Juhl Jensen
Disease Systems Biology
Disease Systems Biology
Lars Juhl Jensen
Large-scale integration of data and text
Large-scale integration of data and text
Lars Juhl Jensen
Network biology
Network biology
Lars Juhl Jensen
Mining molecules from text and data
Mining molecules from text and data
Lars Juhl Jensen
Network biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text mining
Lars Juhl Jensen
Introduction to text mining
Introduction to text mining
Lars Juhl Jensen
Text and data mining
Text and data mining
Lars Juhl Jensen
Turning literature into databases
Turning literature into databases
Lars Juhl Jensen
Network biology: Large-scale data and text mining
Network biology: Large-scale data and text mining
Lars Juhl Jensen
Cellular Network Biology
Cellular Network Biology
Lars Juhl Jensen
Disease systems biology
Disease systems biology
Lars Juhl Jensen
Disease Systems Biology
Disease Systems Biology
Lars Juhl Jensen
Systems biology - Bioinformatics on complete biological systems
Systems biology - Bioinformatics on complete biological systems
Lars Juhl Jensen
Network integration of data and text
Network integration of data and text
Lars Juhl Jensen
Large-scale integration of data and text
Large-scale integration of data and text
Lars Juhl Jensen
Network biology - A basis for large-scale biomedica data mining
Network biology - A basis for large-scale biomedica data mining
Lars Juhl Jensen
Network biology: Large-scale data integration and text mining
Network biology: Large-scale data integration and text mining
Lars Juhl Jensen
The STRING database and related tools
The STRING database and related tools
Lars Juhl Jensen
Large-scale biomedical data and text integration
Large-scale biomedical data and text integration
Lars Juhl Jensen
The pragmatic text miner: It's just another type of poorly standardized data
The pragmatic text miner: It's just another type of poorly standardized data
Lars Juhl Jensen
Large-scale data and text mining
Large-scale data and text mining
Lars Juhl Jensen
Networks of proteins and diseases
Networks of proteins and diseases
Lars Juhl Jensen
One tagger, many uses: Illustrating the power of dictionary-based named entit...
One tagger, many uses: Illustrating the power of dictionary-based named entit...
Lars Juhl Jensen
One tagger, many uses: Simple text-mining strategies for biomedicine
One tagger, many uses: Simple text-mining strategies for biomedicine
Lars Juhl Jensen
More Related Content
Similar to Mining biomedical texts
Network biology
Network biology
Lars Juhl Jensen
Mining molecules from text and data
Mining molecules from text and data
Lars Juhl Jensen
Network biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text mining
Lars Juhl Jensen
Introduction to text mining
Introduction to text mining
Lars Juhl Jensen
Text and data mining
Text and data mining
Lars Juhl Jensen
Turning literature into databases
Turning literature into databases
Lars Juhl Jensen
Network biology: Large-scale data and text mining
Network biology: Large-scale data and text mining
Lars Juhl Jensen
Cellular Network Biology
Cellular Network Biology
Lars Juhl Jensen
Disease systems biology
Disease systems biology
Lars Juhl Jensen
Disease Systems Biology
Disease Systems Biology
Lars Juhl Jensen
Systems biology - Bioinformatics on complete biological systems
Systems biology - Bioinformatics on complete biological systems
Lars Juhl Jensen
Network integration of data and text
Network integration of data and text
Lars Juhl Jensen
Large-scale integration of data and text
Large-scale integration of data and text
Lars Juhl Jensen
Network biology - A basis for large-scale biomedica data mining
Network biology - A basis for large-scale biomedica data mining
Lars Juhl Jensen
Network biology: Large-scale data integration and text mining
Network biology: Large-scale data integration and text mining
Lars Juhl Jensen
The STRING database and related tools
The STRING database and related tools
Lars Juhl Jensen
Large-scale biomedical data and text integration
Large-scale biomedical data and text integration
Lars Juhl Jensen
The pragmatic text miner: It's just another type of poorly standardized data
The pragmatic text miner: It's just another type of poorly standardized data
Lars Juhl Jensen
Large-scale data and text mining
Large-scale data and text mining
Lars Juhl Jensen
Networks of proteins and diseases
Networks of proteins and diseases
Lars Juhl Jensen
Similar to Mining biomedical texts
(20)
Network biology
Network biology
Mining molecules from text and data
Mining molecules from text and data
Network biology: Large-scale biomedical data and text mining
Network biology: Large-scale biomedical data and text mining
Introduction to text mining
Introduction to text mining
Text and data mining
Text and data mining
Turning literature into databases
Turning literature into databases
Network biology: Large-scale data and text mining
Network biology: Large-scale data and text mining
Cellular Network Biology
Cellular Network Biology
Disease systems biology
Disease systems biology
Disease Systems Biology
Disease Systems Biology
Systems biology - Bioinformatics on complete biological systems
Systems biology - Bioinformatics on complete biological systems
Network integration of data and text
Network integration of data and text
Large-scale integration of data and text
Large-scale integration of data and text
Network biology - A basis for large-scale biomedica data mining
Network biology - A basis for large-scale biomedica data mining
Network biology: Large-scale data integration and text mining
Network biology: Large-scale data integration and text mining
The STRING database and related tools
The STRING database and related tools
Large-scale biomedical data and text integration
Large-scale biomedical data and text integration
The pragmatic text miner: It's just another type of poorly standardized data
The pragmatic text miner: It's just another type of poorly standardized data
Large-scale data and text mining
Large-scale data and text mining
Networks of proteins and diseases
Networks of proteins and diseases
More from Lars Juhl Jensen
One tagger, many uses: Illustrating the power of dictionary-based named entit...
One tagger, many uses: Illustrating the power of dictionary-based named entit...
Lars Juhl Jensen
One tagger, many uses: Simple text-mining strategies for biomedicine
One tagger, many uses: Simple text-mining strategies for biomedicine
Lars Juhl Jensen
Extract 2.0: Text-mining-assisted interactive annotation
Extract 2.0: Text-mining-assisted interactive annotation
Lars Juhl Jensen
Network visualization: A crash course on using Cytoscape
Network visualization: A crash course on using Cytoscape
Lars Juhl Jensen
STRING & STITCH: Network integration of heterogeneous data
STRING & STITCH: Network integration of heterogeneous data
Lars Juhl Jensen
Biomedical text mining: Automatic processing of unstructured text
Biomedical text mining: Automatic processing of unstructured text
Lars Juhl Jensen
Medical network analysis: Linking diseases and genes through data and text mi...
Medical network analysis: Linking diseases and genes through data and text mi...
Lars Juhl Jensen
Network Biology: A crash course on STRING and Cytoscape
Network Biology: A crash course on STRING and Cytoscape
Lars Juhl Jensen
Cellular networks
Cellular networks
Lars Juhl Jensen
Cellular Network Biology: Large-scale integration of data and text
Cellular Network Biology: Large-scale integration of data and text
Lars Juhl Jensen
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
Lars Juhl Jensen
STRING & related databases: Large-scale integration of heterogeneous data
STRING & related databases: Large-scale integration of heterogeneous data
Lars Juhl Jensen
Tagger: Rapid dictionary-based named entity recognition
Tagger: Rapid dictionary-based named entity recognition
Lars Juhl Jensen
Network Biology: Large-scale integration of data and text
Network Biology: Large-scale integration of data and text
Lars Juhl Jensen
Medical text mining: Linking diseases, drugs, and adverse reactions
Medical text mining: Linking diseases, drugs, and adverse reactions
Lars Juhl Jensen
Network biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and text
Lars Juhl Jensen
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Lars Juhl Jensen
Network biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and text
Lars Juhl Jensen
Biomarker bioinformatics: Network-based candidate prioritization
Biomarker bioinformatics: Network-based candidate prioritization
Lars Juhl Jensen
The Art of Counting: Scoring and ranking co-occurrences in literature
The Art of Counting: Scoring and ranking co-occurrences in literature
Lars Juhl Jensen
More from Lars Juhl Jensen
(20)
One tagger, many uses: Illustrating the power of dictionary-based named entit...
One tagger, many uses: Illustrating the power of dictionary-based named entit...
One tagger, many uses: Simple text-mining strategies for biomedicine
One tagger, many uses: Simple text-mining strategies for biomedicine
Extract 2.0: Text-mining-assisted interactive annotation
Extract 2.0: Text-mining-assisted interactive annotation
Network visualization: A crash course on using Cytoscape
Network visualization: A crash course on using Cytoscape
STRING & STITCH: Network integration of heterogeneous data
STRING & STITCH: Network integration of heterogeneous data
Biomedical text mining: Automatic processing of unstructured text
Biomedical text mining: Automatic processing of unstructured text
Medical network analysis: Linking diseases and genes through data and text mi...
Medical network analysis: Linking diseases and genes through data and text mi...
Network Biology: A crash course on STRING and Cytoscape
Network Biology: A crash course on STRING and Cytoscape
Cellular networks
Cellular networks
Cellular Network Biology: Large-scale integration of data and text
Cellular Network Biology: Large-scale integration of data and text
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
Statistics on big biomedical data: Methods and pitfalls when analyzing high-t...
STRING & related databases: Large-scale integration of heterogeneous data
STRING & related databases: Large-scale integration of heterogeneous data
Tagger: Rapid dictionary-based named entity recognition
Tagger: Rapid dictionary-based named entity recognition
Network Biology: Large-scale integration of data and text
Network Biology: Large-scale integration of data and text
Medical text mining: Linking diseases, drugs, and adverse reactions
Medical text mining: Linking diseases, drugs, and adverse reactions
Network biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and text
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Medical data and text mining: Linking diseases, drugs, and adverse reactions
Network biology: Large-scale integration of data and text
Network biology: Large-scale integration of data and text
Biomarker bioinformatics: Network-based candidate prioritization
Biomarker bioinformatics: Network-based candidate prioritization
The Art of Counting: Scoring and ranking co-occurrences in literature
The Art of Counting: Scoring and ranking co-occurrences in literature
Recently uploaded
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
Enterprise Knowledge
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
HampshireHUG
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Miguel Araújo
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘
RTylerCroy
Slack Application Development 101 Slides
Slack Application Development 101 Slides
praypatel2
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
Antenna Manufacturer Coco
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Igalia
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
sudhanshuwaghmare1
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
Puma Security, LLC
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
Anna Loughnan Colquhoun
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
Enterprise Knowledge
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
Malak Abu Hammad
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
wesley chun
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Drew Madelung
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
naman860154
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
ThousandEyes
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
Delhi Call girls
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
UK Journal
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
The Digital Insurer
Recently uploaded
(20)
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘
Slack Application Development 101 Slides
Slack Application Development 101 Slides
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
Mining biomedical texts
1.
Mining biomedical texts
Lars Juhl Jensen >10 km
2.
exponential growth
3.
4.
5.
some things are
constant
6.
7.
~45 seconds per
paper
8.
information retrieval
9.
find the relevant
texts
10.
still too much
to read
11.
computer
12.
as smart as
a dog
13.
teach it specific
tricks
14.
15.
16.
named entity recognition
17.
identify the concepts
18.
comprehensive lexicon
19.
small molecules
20.
proteins
21.
cellular components
22.
organisms
23.
diseases
24.
orthographic variation
25.
“ black list”
26.
Reflect.ws
27.
augmented browsing
28.
browser add-on
29.
Pafilis, O’Donoghue, Jensen
et al., Nature Biotechnology , 2009 O’Donoghue et al., Journal of Web Semantics , 2010
30.
Firefox
31.
Internet Explorer
32.
Google Chrome
33.
Safari
34.
Utopia Documents
35.
web services
36.
~150 years of
publishing
37.
38.
dead wood
39.
40.
dead e-wood
41.
added value
42.
collaboration
43.
44.
45.
SciVerse application
46.
47.
48.
49.
50.
51.
STITCH
52.
Kuhn et al.,
Nucleic Acids Research , 2010
53.
curated knowledge
54.
drug targets
55.
pathways
56.
Letunic & Bork,
Trends in Biochemical Sciences , 2008
57.
experimental data
58.
physical interactions
59.
Jensen & Bork,
Science , 2008
60.
text mining
61.
co-mentioning
62.
63.
NLP Natural Language
Processing
64.
65.
abstracts
66.
full text
67.
restricted access
68.
69.
collaboration
70.
electronic patient journals
71.
a hard problem
72.
in Danish
73.
no lexicon
74.
by busy doctors
75.
acronyms
76.
typos
77.
about psychiatric patients
78.
delusions
79.
domain specific system
80.
F20 F200 Negation
Family
81.
diagnoses
82.
patient stratification
83.
Roque et al.,
PLoS Computational Biology , 2011
84.
disease comorbidity
85.
Roque et al.,
PLoS Computational Biology , 2011
86.
medication
87.
adverse drug events
88.
pharmacovigilance
89.
phenotype
90.
genotype
91.
92.
larsjuhljensen
Download now