PDF(Pubmed)
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.
CONCLUSIONS: 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.
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.
CONCLUSIONS: 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.
摘要：
背景：头颈癌（H&NC）是所有癌症病例的重要组成部分。H&NC患者经历了无意的体重减轻，营养状况差，或言语障碍。医疗干预会影响外观并干扰患者对身体的自我感知。由于时间有限，心理咨询负担不起。
方法：我们使用NLP分析基本情绪强度，关于一个人身体的感情，特征性词汇,以及免费笔记中潜在的困难领域。情绪强度研究使用使用单词嵌入开发的扩展NAWL词典。情感分析使用了一种混合方法：情感词典和深度递归网络。由心理肿瘤学家定义的词性标记和领域规则确定了不同的语言特征。使用带有单词极性的词典方法分析了潜在的困难区域，以定义给定区域并使用单词袋表示笔记。这里,我们应用了使用SVD的LSA方法来降维。共有50名需要肠内营养的癌症患者参加了这项研究。
结果：结果证实了H＆NC患者的情绪与身体形象有关的复杂性。在大多数患者中检测到对身体图像的消极态度。研究中提出的方法似乎可以有效地评估身体图像感知障碍，但它不能作为身体形象感知问题的唯一指标。
结论：研究中的主要问题是参与者的年龄范围相当广泛，这解释了词汇的潜在多样性。
结论：患者病情属性的组合，可能使用特定患者的方法来确定，可以指示支持患者的方向，亲戚,直接医务人员,和心理肿瘤学家。
方法：我们使用NLP分析基本情绪强度，关于一个人身体的感情，特征性词汇,以及免费笔记中潜在的困难领域。情绪强度研究使用使用单词嵌入开发的扩展NAWL词典。情感分析使用了一种混合方法：情感词典和深度递归网络。由心理肿瘤学家定义的词性标记和领域规则确定了不同的语言特征。使用带有单词极性的词典方法分析了潜在的困难区域，以定义给定区域并使用单词袋表示笔记。这里,我们应用了使用SVD的LSA方法来降维。共有50名需要肠内营养的癌症患者参加了这项研究。
结果：结果证实了H＆NC患者的情绪与身体形象有关的复杂性。在大多数患者中检测到对身体图像的消极态度。研究中提出的方法似乎可以有效地评估身体图像感知障碍，但它不能作为身体形象感知问题的唯一指标。
结论：研究中的主要问题是参与者的年龄范围相当广泛，这解释了词汇的潜在多样性。
结论：患者病情属性的组合，可能使用特定患者的方法来确定，可以指示支持患者的方向，亲戚,直接医务人员,和心理肿瘤学家。
