@inproceedings{coelho-da-silva-etal-2023-tracking,
title = "Tracking the Evolution of Covid-19 Symptoms through Clinical Conversations",
author = "Coelho Da Silva, Ticiana and
Fernandes De Mac{\^e}do, Jos{\'e} and
Magalh{\~a}es, R{\'e}gis",
editor = "Naumann, Tristan and
Ben Abacha, Asma and
Bethard, Steven and
Roberts, Kirk and
Rumshisky, Anna",
booktitle = "Proceedings of the 5th Clinical Natural Language Processing Workshop",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.clinicalnlp-1.6",
doi = "10.18653/v1/2023.clinicalnlp-1.6",
pages = "41--47",
abstract = "The Coronavirus pandemic has heightened the demand for technological solutions capable of gathering and monitoring data automatically, quickly, and securely. To achieve this need, the Plant{\~a}o Coronavirus chatbot has been made available to the population of Cear{\'a} State in Brazil. This chatbot employs automated symptom detection technology through Natural Language Processing (NLP). The proposal of this work is a symptom tracker, which is a neural network that processes texts and captures symptoms in messages exchanged between citizens of the state and the Plant{\~a}o Coronavirus nurse/doctor, i.e., clinical conversations. The model has the ability to recognize new patterns and has identified a high incidence of altered psychological behaviors, including anguish, anxiety, and sadness, among users who tested positive or negative for Covid-19. As a result, the tool has emphasized the importance of expanding coverage through community mental health services in the state.",
}
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<abstract>The Coronavirus pandemic has heightened the demand for technological solutions capable of gathering and monitoring data automatically, quickly, and securely. To achieve this need, the Plantão Coronavirus chatbot has been made available to the population of Ceará State in Brazil. This chatbot employs automated symptom detection technology through Natural Language Processing (NLP). The proposal of this work is a symptom tracker, which is a neural network that processes texts and captures symptoms in messages exchanged between citizens of the state and the Plantão Coronavirus nurse/doctor, i.e., clinical conversations. The model has the ability to recognize new patterns and has identified a high incidence of altered psychological behaviors, including anguish, anxiety, and sadness, among users who tested positive or negative for Covid-19. As a result, the tool has emphasized the importance of expanding coverage through community mental health services in the state.</abstract>
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%0 Conference Proceedings
%T Tracking the Evolution of Covid-19 Symptoms through Clinical Conversations
%A Coelho Da Silva, Ticiana
%A Fernandes De Macêdo, José
%A Magalhães, Régis
%Y Naumann, Tristan
%Y Ben Abacha, Asma
%Y Bethard, Steven
%Y Roberts, Kirk
%Y Rumshisky, Anna
%S Proceedings of the 5th Clinical Natural Language Processing Workshop
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F coelho-da-silva-etal-2023-tracking
%X The Coronavirus pandemic has heightened the demand for technological solutions capable of gathering and monitoring data automatically, quickly, and securely. To achieve this need, the Plantão Coronavirus chatbot has been made available to the population of Ceará State in Brazil. This chatbot employs automated symptom detection technology through Natural Language Processing (NLP). The proposal of this work is a symptom tracker, which is a neural network that processes texts and captures symptoms in messages exchanged between citizens of the state and the Plantão Coronavirus nurse/doctor, i.e., clinical conversations. The model has the ability to recognize new patterns and has identified a high incidence of altered psychological behaviors, including anguish, anxiety, and sadness, among users who tested positive or negative for Covid-19. As a result, the tool has emphasized the importance of expanding coverage through community mental health services in the state.
%R 10.18653/v1/2023.clinicalnlp-1.6
%U https://aclanthology.org/2023.clinicalnlp-1.6
%U https://doi.org/10.18653/v1/2023.clinicalnlp-1.6
%P 41-47
Markdown (Informal)
[Tracking the Evolution of Covid-19 Symptoms through Clinical Conversations](https://aclanthology.org/2023.clinicalnlp-1.6) (Coelho Da Silva et al., ClinicalNLP 2023)
ACL