scholarly journals Automatic Classification of the Korean Triage Acuity Scale in Simulated Emergency Rooms Using Speech Recognition and Natural Language Processing: a Proof of Concept Study

2021 ◽  
Vol 36 (27) ◽  
Author(s):  
Dongkyun Kim ◽  
Jaehoon Oh ◽  
Heeju Im ◽  
Myeongseong Yoon ◽  
Jiwoo Park ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Speech Recognition ◽  
Natural Language ◽  
Language Processing ◽  
Automatic Classification ◽  
Proof Of Concept ◽  
Emergency Rooms ◽  
Concept Study

scholarly journals Automatic classification of the emotional content of web documents

2021 ◽  
Author(s):  
Alaa Hussainalsaid
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Automatic Classification ◽  
Emotional Content ◽  
Web Pages ◽  
Web Documents ◽  
N Gram

This thesis proposes automatic classification of the emotional content of web documents using Natural Language Processing (NLP) algorithms. We used online articles and general documents to verify the performance of the algorithm, such as general web pages and news articles. The experiments used sentiment analysis that extracts sentiment of web documents. We used unigram and bigram approaches that are known as special types of N-gram, where N=1 and N=2, respectively. The unigram model analyses the probability to hit each word in the corpus independently; however, the bigram model analyses the probability of a word occurring depending on the previous word. Our results show that the unigram model has a better performance compared to the bigram model in terms of automatic classification of the emotional content of web documents.

scholarly journals Automatic classification of the emotional content of web documents

2021 ◽  
Author(s):  
Alaa Hussainalsaid
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Automatic Classification ◽  
Emotional Content ◽  
Web Pages ◽  
Web Documents ◽  
N Gram

This thesis proposes automatic classification of the emotional content of web documents using Natural Language Processing (NLP) algorithms. We used online articles and general documents to verify the performance of the algorithm, such as general web pages and news articles. The experiments used sentiment analysis that extracts sentiment of web documents. We used unigram and bigram approaches that are known as special types of N-gram, where N=1 and N=2, respectively. The unigram model analyses the probability to hit each word in the corpus independently; however, the bigram model analyses the probability of a word occurring depending on the previous word. Our results show that the unigram model has a better performance compared to the bigram model in terms of automatic classification of the emotional content of web documents.

Automatic Classification of Valve Diseases Through Natural Language Processing in Spanish and Active Learning

2021 ◽  
pp. 39-50
Author(s):  
Pablo Pérez-Sánchez ◽  
Víctor Vicente-Palacios ◽  
Manuel Barreiro-Pérez ◽  
Elena Díaz-Peláez ◽  
Antonio Sánchez-Puente ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Active Learning ◽  
Natural Language ◽  
Language Processing ◽  
Automatic Classification ◽  
Valve Diseases

scholarly journals A Natural Language Processing Approach to Measuring Treatment Adherence and Consistency Using Semantic Similarity

AERA Open ◽  
2021 ◽  
Vol 7 ◽  
pp. 233285842110286
Author(s):  
Kylie L. Anglin ◽  
Vivian C. Wong ◽  
Arielle Boguslav
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Semantic Similarity ◽  
Language Processing ◽  
Intervention Implementation ◽  
Proof Of Concept ◽  
Coaching Intervention ◽  
Processing Techniques ◽  
Teacher Coaching ◽  
The Impact

Though there is widespread recognition of the importance of implementation research, evaluators often face intense logistical, budgetary, and methodological challenges in their efforts to assess intervention implementation in the field. This article proposes a set of natural language processing techniques called semantic similarity as an innovative and scalable method of measuring implementation constructs. Semantic similarity methods are an automated approach to quantifying the similarity between texts. By applying semantic similarity to transcripts of intervention sessions, researchers can use the method to determine whether an intervention was delivered with adherence to a structured protocol, and the extent to which an intervention was replicated with consistency across sessions, sites, and studies. This article provides an overview of semantic similarity methods, describes their application within the context of educational evaluations, and provides a proof of concept using an experimental study of the impact of a standardized teacher coaching intervention.

A Comparison of Natural Language Processing Methods for the Classification of Lumbar Spine Imaging Findings Related to Lower Back Pain

2021 ◽  
Author(s):  
Chethan Jujjavarapu ◽  
Vikas Pejaver ◽  
Trevor A. Cohen ◽  
Sean D. Mooney ◽  
Patrick J. Heagerty ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Back Pain ◽  
Lumbar Spine ◽  
Natural Language ◽  
Language Processing ◽  
Lower Back Pain ◽  
Imaging Findings ◽  
Lower Back ◽  
Spine Imaging
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