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Infusing Disease Knowledge into BERT for Health Question …

Web%0 Conference Proceedings %T Infusing Disease Knowledge into BERT for Health Question Answering, Medical Inference and Disease Name Recognition %A …

Actived: 5 days ago

URL: https://aclanthology.org/2020.emnlp-main.372/

Explainable Automated Fact-Checking for Public Health Claims

Web%0 Conference Proceedings %T Explainable Automated Fact-Checking for Public Health Claims %A Kotonya, Neema %A Toni, Francesca %Y Webber, Bonnie %Y …

Category:  Health Go Health

Applications of Natural Language Processing in Clinical Research …

Web10.18653/v1/N19-5006. Bibkey: wang-etal-2019-applications. Cite (ACL): Yanshan Wang, Ahmad Tafti, Sunghwan Sohn, and Rui Zhang. 2019. Applications of …

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An Integrative Survey on Mental Health Conversational Agents to …

Web%0 Conference Proceedings %T An Integrative Survey on Mental Health Conversational Agents to Bridge Computer Science and Medical Perspectives %A Cho, …

Category:  Medical Go Health

Overview of the Fourth Social Media Mining for Health (SMM4H) …

WebDavy Weissenbacher, Abeed Sarker, Arjun Magge, Ashlynn Daughton, Karen O’Connor, Michael J. Paul, Graciela Gonzalez-Hernandez. Proceedings of the Fourth …

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Ethical Research Protocols for Social Media Health Research

WebWe provide practical suggestions in the form of guidelines for researchers working with social media data in health research. These guidelines can inform an IRB …

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Language and Mental Health: Measures of Emotion Dynamics …

Web%0 Conference Proceedings %T Language and Mental Health: Measures of Emotion Dynamics from Text as Linguistic Biosocial Markers %A Teodorescu, Daniela …

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SMHD: a Large-Scale Resource for Exploring Online Language …

WebAbstract Mental health is a significant and growing public health concern. As language usage can be leveraged to obtain crucial insights into mental health …

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Dr ChatGPT tell me what I want to hear: How different prompts …

Web%0 Conference Proceedings %T Dr ChatGPT tell me what I want to hear: How different prompts impact health answer correctness %A Koopman, Bevan %A …

Category:  Health Go Health

Towards Interpretable Mental Health Analysis with Large …

Web%0 Conference Proceedings %T Towards Interpretable Mental Health Analysis with Large Language Models %A Yang, Kailai %A Ji, Shaoxiong %A Zhang, …

Category:  Health Go Health

EmoMent: An Emotion Annotated Mental Health Corpus from Two …

WebEmoMent corpus achieved ‘very good’ inter-annotator agreement of 98.3% (i.e. % with two or more agreement) and Fleiss’ Kappa of 0.82. Our RoBERTa based …

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Improving Biomedical Pretrained Language Models with Knowledge

WebLeveraging this knowledge can benefit a variety of downstream tasks such as named entity recognition and relation extraction. To this end, we propose KeBioLM, a …

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SMHD: a Large-Scale Resource for Exploring Online Language …

Web1487 conditions while Yates et al. (2017) focus only on depression. We explore classification methods for identifying mental health conditions through social media …

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PsyQA: A Chinese Dataset for Generating Long Counseling Text for …

Web%0 Conference Proceedings %T PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support %A Sun, Hao %A Lin, Zhenru %A …

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Towards Enhancing Health Coaching Dialogue in Low-Resource …

Web@inproceedings{zhou-etal-2022-towards, title = "Towards Enhancing Health Coaching Dialogue in Low-Resource Settings", author = "Zhou, Yue and Di Eugenio, …

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How to leverage the multimodal EHR data for better medical …

WebTherefore, in this paper, we first extract the accompanying clinical notes from EHR and propose a method to integrate these data, we also comprehensively study the …

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MedicalSum: A Guided Clinical Abstractive Summarization …

Webwhere swj 2 R D s is a 1-hot vector correspond- ing to the semantic type of the medical word w j and p(j) 2 R d is the position embedding of the jth token in the sentence. Finally, E 2 …

Category:  Medical Go Health

Towards Interpretable Mental Health Analysis with Large …

WebLLaMA (Touvron et al., 2023) is a set of open-source LLMs developed by Meta AI, which are generatively pre-trained on entirely publicly available datasets. We test the zero-shot …

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