Pathology and Social Media
Pathophysiology
Carcinogenesis, Hallmarks of Cancer

Text Editing

Text Editing

Text Editing

  • Replace with a Subscript

http://www.brainbell.com/tutorials/ms-office/Word/Replace_With_A_Subscript.htm

Opinion Mining, Sentiment Analysis, and Opinion Spam Detection

https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html

Statistics for Social Data

http://ptrckprry.com/course/ssd/

Opinion Mining, Sentiment Analysis, and Opinion Spam Detection

https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html

Statistics for Social Data

http://ptrckprry.com/course/ssd/

Opinion Mining, Sentiment Analysis, and Opinion Spam Detection

https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html

Statistics for Social Data

http://ptrckprry.com/course/ssd/

Opinion Mining, Sentiment Analysis, and Opinion Spam Detection

https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html

Text Mining Courses

http://ptrckprry.com/course/ssd/

Opinion Mining, Sentiment Analysis, and Opinion Spam Detection

https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html

Text Mining Journal Articles

  • E-mail Address Harvesting on PubMed—A Call for Responsible Handling of E-mail Addresses

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3068898/

  • Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository.

https://www.ncbi.nlm.nih.gov/pubmed/28269893

  • Text mining of cancer-related information: Review of current status and future directions

http://www.sciencedirect.com/science/article/pii/S1386505614001105

  • Classification of Cancer-related Death Certificates using Machine Learning

https://www.researchgate.net/publication/237071357_Classification_of_Cancer-related_Death_Certificates_using_Machine_Learning

  • E-mail Address Harvesting on PubMed—A Call for Responsible Handling of E-mail Addresses

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3068898/

  • Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository.

https://www.ncbi.nlm.nih.gov/pubmed/28269893

  • Text mining of cancer-related information: Review of current status and future directions

http://www.sciencedirect.com/science/article/pii/S1386505614001105

  • Classification of Cancer-related Death Certificates using Machine Learning

https://www.researchgate.net/publication/237071357_Classification_of_Cancer-related_Death_Certificates_using_Machine_Learning

  • E-mail Address Harvesting on PubMed—A Call for Responsible Handling of E-mail Addresses

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3068898/

  • Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository.

https://www.ncbi.nlm.nih.gov/pubmed/28269893

  • Text mining of cancer-related information: Review of current status and future directions

http://www.sciencedirect.com/science/article/pii/S1386505614001105

  • Classification of Cancer-related Death Certificates using Machine Learning

https://www.researchgate.net/publication/237071357_Classification_of_Cancer-related_Death_Certificates_using_Machine_Learning

  • E-mail Address Harvesting on PubMed—A Call for Responsible Handling of E-mail Addresses

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3068898/

  • Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository.

https://www.ncbi.nlm.nih.gov/pubmed/28269893

  • Text mining of cancer-related information: Review of current status and future directions

http://www.sciencedirect.com/science/article/pii/S1386505614001105

  • Classification of Cancer-related Death Certificates using Machine Learning

https://www.researchgate.net/publication/237071357_Classification_of_Cancer-related_Death_Certificates_using_Machine_Learning

Text Mining Journal Articles

  • E-mail Address Harvesting on PubMed—A Call for Responsible Handling of E-mail Addresses

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3068898/

  • Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository.

https://www.ncbi.nlm.nih.gov/pubmed/28269893

  • Text mining of cancer-related information: Review of current status and future directions

http://www.sciencedirect.com/science/article/pii/S1386505614001105

  • Classification of Cancer-related Death Certificates using Machine Learning

https://www.researchgate.net/publication/237071357_Classification_of_Cancer-related_Death_Certificates_using_Machine_Learning

  • Text Mining General

  • Text Mining General

Text Mining Orange

Text Mining Orange

Data sets for author name disambiguation: an empirical analysis and a new resource

https://link.springer.com/article/10.1007/s11192-017-2363-5?wt_mc=alerts.TOCjournals

A theoretical model of the relationship between the h-index and other simple citation indicators

https://link.springer.com/article/10.1007/s11192-017-2351-9?wt_mc=alerts.TOCjournals

Data sets for author name disambiguation: an empirical analysis and a new resource

https://link.springer.com/article/10.1007/s11192-017-2363-5?wt_mc=alerts.TOCjournals

A theoretical model of the relationship between the h-index and other simple citation indicators

https://link.springer.com/article/10.1007/s11192-017-2351-9?wt_mc=alerts.TOCjournals

Text Mining PubMed

Text Mining PubMed

Data sets for author name disambiguation: an empirical analysis and a new resource

https://link.springer.com/article/10.1007/s11192-017-2363-5?wt_mc=alerts.TOCjournals

A theoretical model of the relationship between the h-index and other simple citation indicators

https://link.springer.com/article/10.1007/s11192-017-2351-9?wt_mc=alerts.TOCjournals

Data sets for author name disambiguation: an empirical analysis and a new resource

https://link.springer.com/article/10.1007/s11192-017-2363-5?wt_mc=alerts.TOCjournals

A theoretical model of the relationship between the h-index and other simple citation indicators

https://link.springer.com/article/10.1007/s11192-017-2351-9?wt_mc=alerts.TOCjournals

Text Mining PubMed

Data sets for author name disambiguation: an empirical analysis and a new resource

https://link.springer.com/article/10.1007/s11192-017-2363-5?wt_mc=alerts.TOCjournals

A theoretical model of the relationship between the h-index and other simple citation indicators

https://link.springer.com/article/10.1007/s11192-017-2351-9?wt_mc=alerts.TOCjournals

Text Mining R

  • Analyzing Google Trends Data in R

https://www.displayr.com/extracting-google-trends-data-in-r/?utm_source=Facebook&utm_medium=R Programming&utm_campaign=google trends

  • Analyzing Google Trends Data in R

https://www.displayr.com/extracting-google-trends-data-in-r/?utm_source=Facebook&utm_medium=R Programming&utm_campaign=google trends

  • Analyzing Google Trends Data in R

https://www.displayr.com/extracting-google-trends-data-in-r/?utm_source=Facebook&utm_medium=R Programming&utm_campaign=google trends

  • Analyzing Google Trends Data in R

https://www.displayr.com/extracting-google-trends-data-in-r/?utm_source=Facebook&utm_medium=R Programming&utm_campaign=google trends

Text Mining R

  • Analyzing Google Trends Data in R

https://www.displayr.com/extracting-google-trends-data-in-r/?utm_source=Facebook&utm_medium=R Programming&utm_campaign=google trends

Text Mining Related Web Sites

  • import.io

https://www.import.io

  • parsehub

https://www.parsehub.com/

  • Regular Expression 101 is a very nice tool to identify regex codes for text mining

https://twitter.com/regex101

https://regex101.com/

  • RegExr is an online tool to learn, build & test Regular Expressions (RegEx / RegExp).

https://regexr.com/

  • Downloadable statistical models for spaCy to predict and assign linguistic features

https://spacy.io/models/

  • Industrial-Strength Natural Language Processing

https://spacy.io/

  • import.io

https://www.import.io

  • parsehub

https://www.parsehub.com/

  • Regular Expression 101 is a very nice tool to identify regex codes for text mining

https://twitter.com/regex101

https://regex101.com/

  • RegExr is an online tool to learn, build & test Regular Expressions (RegEx / RegExp).

https://regexr.com/

  • Downloadable statistical models for spaCy to predict and assign linguistic features

https://spacy.io/models/

  • Industrial-Strength Natural Language Processing

https://spacy.io/

  • import.io

https://www.import.io

  • parsehub

https://www.parsehub.com/

  • Regular Expression 101 is a very nice tool to identify regex codes for text mining

https://twitter.com/regex101

https://regex101.com/

  • RegExr is an online tool to learn, build & test Regular Expressions (RegEx / RegExp).

https://regexr.com/

  • Downloadable statistical models for spaCy to predict and assign linguistic features

https://spacy.io/models/

  • Industrial-Strength Natural Language Processing

https://spacy.io/

  • import.io

https://www.import.io

  • parsehub

https://www.parsehub.com/

  • Regular Expression 101 is a very nice tool to identify regex codes for text mining

https://twitter.com/regex101

https://regex101.com/

  • RegExr is an online tool to learn, build & test Regular Expressions (RegEx / RegExp).

https://regexr.com/

  • Downloadable statistical models for spaCy to predict and assign linguistic features

https://spacy.io/models/

  • Industrial-Strength Natural Language Processing

https://spacy.io/

Text Mining Related Web Sites

  • import.io

https://www.import.io

  • parsehub

https://www.parsehub.com/

  • Regular Expression 101 is a very nice tool to identify regex codes for text mining

https://twitter.com/regex101

https://regex101.com/

  • RegExr is an online tool to learn, build & test Regular Expressions (RegEx / RegExp).

https://regexr.com/

  • Downloadable statistical models for spaCy to predict and assign linguistic features

https://spacy.io/models/

  • Industrial-Strength Natural Language Processing

https://spacy.io/

Text Mining Turkish

  • The Lucene stopwords.txt source code

https://alvinalexander.com/java/jwarehouse/lucene/contrib/analyzers/common/src/resources/org/apache/lucene/analysis/tr/stopwords.txt.shtml

http://www.turkceogretimi.com/Genel-Konular/article/541-turkce-etkisiz-kelimeler-stop-words-listesi-11/35

https://github.com/crodas/TextRank/blob/master/lib/TextRank/Stopword/turkish-stopwords.txt

https://github.com/stopwords-iso/stopwords-tr

https://github.com/tkorkunckaya/Turkish-Stopwords

trstop

  • The Lucene stopwords.txt source code

https://alvinalexander.com/java/jwarehouse/lucene/contrib/analyzers/common/src/resources/org/apache/lucene/analysis/tr/stopwords.txt.shtml

http://www.turkceogretimi.com/Genel-Konular/article/541-turkce-etkisiz-kelimeler-stop-words-listesi-11/35

https://github.com/crodas/TextRank/blob/master/lib/TextRank/Stopword/turkish-stopwords.txt

https://github.com/stopwords-iso/stopwords-tr

https://github.com/tkorkunckaya/Turkish-Stopwords

trstop

  • The Lucene stopwords.txt source code

https://alvinalexander.com/java/jwarehouse/lucene/contrib/analyzers/common/src/resources/org/apache/lucene/analysis/tr/stopwords.txt.shtml

http://www.turkceogretimi.com/Genel-Konular/article/541-turkce-etkisiz-kelimeler-stop-words-listesi-11/35

https://github.com/crodas/TextRank/blob/master/lib/TextRank/Stopword/turkish-stopwords.txt

https://github.com/stopwords-iso/stopwords-tr

https://github.com/tkorkunckaya/Turkish-Stopwords

trstop

  • The Lucene stopwords.txt source code

https://alvinalexander.com/java/jwarehouse/lucene/contrib/analyzers/common/src/resources/org/apache/lucene/analysis/tr/stopwords.txt.shtml

http://www.turkceogretimi.com/Genel-Konular/article/541-turkce-etkisiz-kelimeler-stop-words-listesi-11/35

https://github.com/crodas/TextRank/blob/master/lib/TextRank/Stopword/turkish-stopwords.txt

https://github.com/stopwords-iso/stopwords-tr

https://github.com/tkorkunckaya/Turkish-Stopwords

trstop

Text Mining Turkish

  • The Lucene stopwords.txt source code

https://alvinalexander.com/java/jwarehouse/lucene/contrib/analyzers/common/src/resources/org/apache/lucene/analysis/tr/stopwords.txt.shtml

http://www.turkceogretimi.com/Genel-Konular/article/541-turkce-etkisiz-kelimeler-stop-words-listesi-11/35

https://github.com/crodas/TextRank/blob/master/lib/TextRank/Stopword/turkish-stopwords.txt

https://github.com/stopwords-iso/stopwords-tr

https://github.com/tkorkunckaya/Turkish-Stopwords

trstop

Text Mining Twitter

  • Quick guide to mining twitter with R

https://sites.google.com/site/miningtwitter/home

  • Symplur

https://www.symplur.com/healthcare-hashtags/pathology/

https://www.symplur.com/blog/introducing-pathology-hashtag-ontology/

  • Symplur Signals for Research

https://www.youtube.com/watch?v=7mmQCFjpDtk&list=WL&index=15

  • Quick guide to mining twitter with R

https://sites.google.com/site/miningtwitter/home

  • Symplur

https://www.symplur.com/healthcare-hashtags/pathology/

https://www.symplur.com/blog/introducing-pathology-hashtag-ontology/

  • Symplur Signals for Research

https://www.youtube.com/watch?v=7mmQCFjpDtk&list=WL&index=15

  • Quick guide to mining twitter with R

https://sites.google.com/site/miningtwitter/home

  • Symplur

https://www.symplur.com/healthcare-hashtags/pathology/

https://www.symplur.com/blog/introducing-pathology-hashtag-ontology/

  • Symplur Signals for Research

https://www.youtube.com/watch?v=7mmQCFjpDtk&list=WL&index=15

  • Quick guide to mining twitter with R

https://sites.google.com/site/miningtwitter/home

  • Symplur

https://www.symplur.com/healthcare-hashtags/pathology/

https://www.symplur.com/blog/introducing-pathology-hashtag-ontology/

  • Symplur Signals for Research

https://www.youtube.com/watch?v=7mmQCFjpDtk&list=WL&index=15

Text Mining Twitter

  • Quick guide to mining twitter with R

https://sites.google.com/site/miningtwitter/home

  • Symplur

https://www.symplur.com/healthcare-hashtags/pathology/

https://www.symplur.com/blog/introducing-pathology-hashtag-ontology/

  • Symplur Signals for Research

https://www.youtube.com/watch?v=7mmQCFjpDtk&list=WL&index=15

Text Mining Videos

  • Text Mining (part 1) - Import Text into R (single document)

https://www.youtube.com/watch?v=fga5gLtFQs0&index=2&list=WL

  • Text Mining (part 2) - Cleaning Text Data in R (single document)

https://www.youtube.com/watch?v=gtQWMxWzs_M&list=WL&index=2

  • Text Mining (part 3) - Sentiment Analysis and Wordcloud in R (single document)

https://www.youtube.com/watch?v=JM_J7ufS-BU&t=0s

  • Text Mining (part4) - Postive and Negative Terms for Sentiment Analysis in R

https://www.youtube.com/watch?v=WfoVINuxIJA&index=11&list=WL

http://ptrckprry.com/course/ssd/data/positive-words.txt

http://ptrckprry.com/course/ssd/data/negative-words.txt

  • Text Mining (part 5) - Import a Corpus in R

https://www.youtube.com/watch?v=pFinlXYLZ-A&list=WL&index=14

  • Text Mining (part 6) - Cleaning Corpus text in R

https://www.youtube.com/watch?v=jCrQYOsAcv4&list=WL&index=24

--

    • N-gram word clouds in R ! Learn it in 5 minutes !

https://www.youtube.com/watch?v=HellsQ2JF2k&feature=youtu.be

  • Word Cloud in R - Learn it in 4 minutes !

https://www.youtube.com/watch?v=oVVvG035vQc

if you get error try this:

corpus <- tm_map(corpus,content_transformer(function(x) iconv(x, "latin1", "ASCII", sub="")))

--

  • Text Mining (part 1) - Import Text into R (single document)

https://www.youtube.com/watch?v=fga5gLtFQs0&index=2&list=WL

  • Text Mining (part 2) - Cleaning Text Data in R (single document)

https://www.youtube.com/watch?v=gtQWMxWzs_M&list=WL&index=2

  • Text Mining (part 3) - Sentiment Analysis and Wordcloud in R (single document)

https://www.youtube.com/watch?v=JM_J7ufS-BU&t=0s

  • Text Mining (part4) - Postive and Negative Terms for Sentiment Analysis in R

https://www.youtube.com/watch?v=WfoVINuxIJA&index=11&list=WL

http://ptrckprry.com/course/ssd/data/positive-words.txt

http://ptrckprry.com/course/ssd/data/negative-words.txt

  • Text Mining (part 5) - Import a Corpus in R

https://www.youtube.com/watch?v=pFinlXYLZ-A&list=WL&index=14

  • Text Mining (part 6) - Cleaning Corpus text in R

https://www.youtube.com/watch?v=jCrQYOsAcv4&list=WL&index=24

--

  • N-gram word clouds in R ! Learn it in 5 minutes !

https://www.youtube.com/watch?v=HellsQ2JF2k&feature=youtu.be

  • Word Cloud in R - Learn it in 4 minutes !

https://www.youtube.com/watch?v=oVVvG035vQc

if you get error try this:

corpus <- tm_map(corpus,content_transformer(function(x) iconv(x, "latin1", "ASCII", sub="")))

--

  • Text Mining (part 1) - Import Text into R (single document)

https://www.youtube.com/watch?v=fga5gLtFQs0&index=2&list=WL

  • Text Mining (part 2) - Cleaning Text Data in R (single document)

https://www.youtube.com/watch?v=gtQWMxWzs_M&list=WL&index=2

  • Text Mining (part 3) - Sentiment Analysis and Wordcloud in R (single document)

https://www.youtube.com/watch?v=JM_J7ufS-BU&t=0s

  • Text Mining (part4) - Postive and Negative Terms for Sentiment Analysis in R

https://www.youtube.com/watch?v=WfoVINuxIJA&index=11&list=WL

http://ptrckprry.com/course/ssd/data/positive-words.txt

http://ptrckprry.com/course/ssd/data/negative-words.txt

  • Text Mining (part 5) - Import a Corpus in R

https://www.youtube.com/watch?v=pFinlXYLZ-A&list=WL&index=14

  • Text Mining (part 6) - Cleaning Corpus text in R

https://www.youtube.com/watch?v=jCrQYOsAcv4&list=WL&index=24

--

  • N-gram word clouds in R ! Learn it in 5 minutes !

https://www.youtube.com/watch?v=HellsQ2JF2k&feature=youtu.be

  • Word Cloud in R - Learn it in 4 minutes !

https://www.youtube.com/watch?v=oVVvG035vQc

if you get error try this:

corpus <- tm_map(corpus,content_transformer(function(x) iconv(x, "latin1", "ASCII", sub="")))

--

  • Text Mining (part 1) - Import Text into R (single document)

https://www.youtube.com/watch?v=fga5gLtFQs0&index=2&list=WL

  • Text Mining (part 2) - Cleaning Text Data in R (single document)

https://www.youtube.com/watch?v=gtQWMxWzs_M&list=WL&index=2

  • Text Mining (part 3) - Sentiment Analysis and Wordcloud in R (single document)

https://www.youtube.com/watch?v=JM_J7ufS-BU&t=0s

  • Text Mining (part4) - Postive and Negative Terms for Sentiment Analysis in R

https://www.youtube.com/watch?v=WfoVINuxIJA&index=11&list=WL

http://ptrckprry.com/course/ssd/data/positive-words.txt

http://ptrckprry.com/course/ssd/data/negative-words.txt

  • Text Mining (part 5) - Import a Corpus in R

https://www.youtube.com/watch?v=pFinlXYLZ-A&list=WL&index=14

  • Text Mining (part 6) - Cleaning Corpus text in R

https://www.youtube.com/watch?v=jCrQYOsAcv4&list=WL&index=24

--

  • N-gram word clouds in R ! Learn it in 5 minutes !

https://www.youtube.com/watch?v=HellsQ2JF2k&feature=youtu.be

  • Word Cloud in R - Learn it in 4 minutes !

https://www.youtube.com/watch?v=oVVvG035vQc

if you get error try this:

corpus <- tm_map(corpus,content_transformer(function(x) iconv(x, "latin1", "ASCII", sub="")))

--

Text Mining Videos

  • Text Mining (part 1) - Import Text into R (single document)

https://www.youtube.com/watch?v=fga5gLtFQs0&index=2&list=WL

  • Text Mining (part 2) - Cleaning Text Data in R (single document)

https://www.youtube.com/watch?v=gtQWMxWzs_M&list=WL&index=2

  • Text Mining (part 3) - Sentiment Analysis and Wordcloud in R (single document)

https://www.youtube.com/watch?v=JM_J7ufS-BU&t=0s

  • Text Mining (part4) - Postive and Negative Terms for Sentiment Analysis in R

https://www.youtube.com/watch?v=WfoVINuxIJA&index=11&list=WL

http://ptrckprry.com/course/ssd/data/positive-words.txt

http://ptrckprry.com/course/ssd/data/negative-words.txt

  • Text Mining (part 5) - Import a Corpus in R

https://www.youtube.com/watch?v=pFinlXYLZ-A&list=WL&index=14

  • Text Mining (part 6) - Cleaning Corpus text in R

https://www.youtube.com/watch?v=jCrQYOsAcv4&list=WL&index=24

--

    • N-gram word clouds in R ! Learn it in 5 minutes !

https://www.youtube.com/watch?v=HellsQ2JF2k&feature=youtu.be

  • Word Cloud in R - Learn it in 4 minutes !

https://www.youtube.com/watch?v=oVVvG035vQc

if you get error try this:

corpus <- tm_map(corpus,content_transformer(function(x) iconv(x, "latin1", "ASCII", sub="")))

--

  • Text Mining General

Contents
Text Editing
Text Editing
Opinion Mining, Sentiment Analysis, and Opinion Spam Detection
Statistics for Social Data
Opinion Mining, Sentiment Analysis, and Opinion Spam Detection
Statistics for Social Data
Opinion Mining, Sentiment Analysis, and Opinion Spam Detection
Statistics for Social Data
Opinion Mining, Sentiment Analysis, and Opinion Spam Detection
Text Mining Courses
Opinion Mining, Sentiment Analysis, and Opinion Spam Detection
Text Mining Journal Articles
Text Mining Journal Articles
Text Mining Orange
Text Mining Orange
Data sets for author name disambiguation: an empirical analysis and a new resource
A theoretical model of the relationship between the h-index and other simple citation indicators
Data sets for author name disambiguation: an empirical analysis and a new resource
A theoretical model of the relationship between the h-index and other simple citation indicators
Text Mining PubMed
Text Mining PubMed
Data sets for author name disambiguation: an empirical analysis and a new resource
A theoretical model of the relationship between the h-index and other simple citation indicators
Data sets for author name disambiguation: an empirical analysis and a new resource
A theoretical model of the relationship between the h-index and other simple citation indicators
Text Mining PubMed
Data sets for author name disambiguation: an empirical analysis and a new resource
A theoretical model of the relationship between the h-index and other simple citation indicators
Text Mining R
Text Mining R
Text Mining Related Web Sites
Text Mining Related Web Sites
Text Mining Turkish
trstop
https://github.com/ahmetax/trstop
trstop
https://github.com/ahmetax/trstop
trstop
https://github.com/ahmetax/trstop
trstop
https://github.com/ahmetax/trstop
Text Mining Turkish
trstop
https://github.com/ahmetax/trstop
Text Mining Twitter
Text Mining Twitter
Text Mining Videos
Text Mining Videos