n-Gram based language processing using Twitter dataset to identify COVID-19 patients Article Swipe

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Nidal Nasser , Lutful Karim , Ahmed El Ouadrhiri , Asmaa Ali , Najeeb Alam Khan ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.1016/j.scs.2021.103048

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Artificial Intelligence

Infectious Diseases (Medical Specialty)

Bacteria

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Coronavirus disease 2019 (COVID-19) n-gram Gram Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 2019-20 coronavirus outbreak Computer science Natural language processing Artificial intelligence Medicine Language model Virology Biology Pathology Outbreak Infectious disease (medical specialty) Bacteria Disease Genetics

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Type: article
Language: en
Landing Page: https://doi.org/10.1016/j.scs.2021.103048
OA Status: green
Cited By: 30
References: 25
Related Works: 10
OpenAlex ID: https://openalex.org/W3164920349

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DOI: https://doi.org/10.1016/j.scs.2021.103048

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Title: n-Gram based language processing using Twitter dataset to identify COVID-19 patients

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Language: en

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Publication year: 2021

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Publication date: 2021-05-25

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Authors: Nidal Nasser, Lutful Karim, Ahmed El Ouadrhiri, Asmaa Ali, Najeeb Alam Khan

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Landing page: https://doi.org/10.1016/j.scs.2021.103048

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Concepts: Coronavirus disease 2019 (COVID-19), n-gram, Gram, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2019-20 coronavirus outbreak, Computer science, Natural language processing, Artificial intelligence, Medicine, Language model, Virology, Biology, Pathology, Outbreak, Infectious disease (medical specialty), Bacteria, Disease, Genetics

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Cited by: 30

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referenced_works_count	25
abstract_inverted_index
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corresponding_author_ids	https://openalex.org/A5091515770
countries_distinct_count	3
institutions_distinct_count	5
corresponding_institution_ids	https://openalex.org/I134359838
sustainable_development_goals[0].id	https://metadata.un.org/sdg/4
sustainable_development_goals[0].score	0.6299999952316284
sustainable_development_goals[0].display_name	Quality Education
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