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The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers

SIMPLE SUMMARY: Psychological assessment of a cancer patient is a challenge due to the difficulty of the issues raised and, additionally, the lack of a sufficient number of psycho-oncologists. The article proposes a minimally invasive automatic method of this assessment using a note prepared by the...

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Autores principales: Gliwska, Elwira, Barańska, Klaudia, Maćkowska, Stella, Różańska, Agnieszka, Sobol, Adrianna, Spinczyk, Dominik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670138/
https://www.ncbi.nlm.nih.gov/pubmed/38001696
http://dx.doi.org/10.3390/cancers15225437
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author Gliwska, Elwira
Barańska, Klaudia
Maćkowska, Stella
Różańska, Agnieszka
Sobol, Adrianna
Spinczyk, Dominik
author_facet Gliwska, Elwira
Barańska, Klaudia
Maćkowska, Stella
Różańska, Agnieszka
Sobol, Adrianna
Spinczyk, Dominik
author_sort Gliwska, Elwira
collection PubMed
description SIMPLE SUMMARY: Psychological assessment of a cancer patient is a challenge due to the difficulty of the issues raised and, additionally, the lack of a sufficient number of psycho-oncologists. The article proposes a minimally invasive automatic method of this assessment using a note prepared by the patient about his body image. The proposed method allows you to determine the general attitude, the intensity of the five basic emotions (happiness, fear, sadness, anger, disgust), and potential areas of difficulty in terms of: body image, self-esteem, and acceptance of the environment. The combination of the attributes of patient’s condition determined by the method can indicate the direction of support for the patient, relatives, direct medical personnel, and psycho-oncologists. ABSTRACT: Background: Head and neck cancers (H&NCs) constitute a significant part of all cancer cases. H&NC patients experience unintentional weight loss, poor nutritional status, or speech disorders. Medical interventions affect appearance and interfere with patients’ self-perception of their bodies. Psychological consultations are not affordable due to limited time. Methods: We used NLP to analyze the basic emotion intensity, sentiment about one’s body, characteristic vocabulary, and potential areas of difficulty in free notes. The emotion intensity research uses the extended NAWL dictionary developed using word embedding. The sentiment analysis used a hybrid approach: a sentiment dictionary and a deep recursive network. The part-of-speech tagging and domain rules defined by a psycho-oncologist determine the distinct language traits. Potential areas of difficulty were analyzed using the dictionaries method with word polarity to define a given area and the presentation of a note using bag-of-words. Here, we applied the LSA method using SVD to reduce dimensionality. A total of 50 cancer patients requiring enteral nutrition participated in the study. Results: The results confirmed the complexity of emotions in patients with H&NC in relation to their body image. A negative attitude towards body image was detected in most of the patients. The method presented in the study appeared to be effective in assessing body image perception disturbances, but it cannot be used as the sole indicator of body image perception issues. Limitations: The main problem in the research was the fairly wide age range of participants, which explains the potential diversity of vocabulary. Conclusions: The combination of the attributes of a patient’s condition, possible to determine using the method for a specific patient, can indicate the direction of support for the patient, relatives, direct medical personnel, and psycho-oncologists.
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spelling pubmed-106701382023-11-16 The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers Gliwska, Elwira Barańska, Klaudia Maćkowska, Stella Różańska, Agnieszka Sobol, Adrianna Spinczyk, Dominik Cancers (Basel) Article SIMPLE SUMMARY: Psychological assessment of a cancer patient is a challenge due to the difficulty of the issues raised and, additionally, the lack of a sufficient number of psycho-oncologists. The article proposes a minimally invasive automatic method of this assessment using a note prepared by the patient about his body image. The proposed method allows you to determine the general attitude, the intensity of the five basic emotions (happiness, fear, sadness, anger, disgust), and potential areas of difficulty in terms of: body image, self-esteem, and acceptance of the environment. The combination of the attributes of patient’s condition determined by the method can indicate the direction of support for the patient, relatives, direct medical personnel, and psycho-oncologists. ABSTRACT: Background: Head and neck cancers (H&NCs) constitute a significant part of all cancer cases. H&NC patients experience unintentional weight loss, poor nutritional status, or speech disorders. Medical interventions affect appearance and interfere with patients’ self-perception of their bodies. Psychological consultations are not affordable due to limited time. Methods: We used NLP to analyze the basic emotion intensity, sentiment about one’s body, characteristic vocabulary, and potential areas of difficulty in free notes. The emotion intensity research uses the extended NAWL dictionary developed using word embedding. The sentiment analysis used a hybrid approach: a sentiment dictionary and a deep recursive network. The part-of-speech tagging and domain rules defined by a psycho-oncologist determine the distinct language traits. Potential areas of difficulty were analyzed using the dictionaries method with word polarity to define a given area and the presentation of a note using bag-of-words. Here, we applied the LSA method using SVD to reduce dimensionality. A total of 50 cancer patients requiring enteral nutrition participated in the study. Results: The results confirmed the complexity of emotions in patients with H&NC in relation to their body image. A negative attitude towards body image was detected in most of the patients. The method presented in the study appeared to be effective in assessing body image perception disturbances, but it cannot be used as the sole indicator of body image perception issues. Limitations: The main problem in the research was the fairly wide age range of participants, which explains the potential diversity of vocabulary. Conclusions: The combination of the attributes of a patient’s condition, possible to determine using the method for a specific patient, can indicate the direction of support for the patient, relatives, direct medical personnel, and psycho-oncologists. MDPI 2023-11-16 /pmc/articles/PMC10670138/ /pubmed/38001696 http://dx.doi.org/10.3390/cancers15225437 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gliwska, Elwira
Barańska, Klaudia
Maćkowska, Stella
Różańska, Agnieszka
Sobol, Adrianna
Spinczyk, Dominik
The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers
title The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers
title_full The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers
title_fullStr The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers
title_full_unstemmed The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers
title_short The Use of Natural Language Processing for Computer-Aided Diagnostics and Monitoring of Body Image Perception in Patients with Cancers
title_sort use of natural language processing for computer-aided diagnostics and monitoring of body image perception in patients with cancers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10670138/
https://www.ncbi.nlm.nih.gov/pubmed/38001696
http://dx.doi.org/10.3390/cancers15225437
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