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Mental health is a critical issue in modern society, and mental disorders could sometimes turn to suicidal ideation without adequate treatment.
ClinicalBERT: Modeling clinical notes and predicting hospital readmission
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RoBERTa: A robustly optimized bert pretraining approach
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Adam: A Method for Stochastic Optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Clpsych 2015 shared task: Depression and ptsd on twitter
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A test collection for research on depression and language use
David E Losada and Fabio Crestani. 2016 · 2016
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Natural language processing in mental health applications using non-clinical texts
Rafael A Calvo, David N Milne, M Sazzad Hussain, and Helen Christensen. 2017 · 2017
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Personal sensing: understanding mental health using ubiquitous sensors and machine learning
David C Mohr, Mi Zhang, and Stephen M Schueller. 2017 · 2017
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Supervised learning for suicidal ideation detection in online user content
Shaoxiong Ji, Celina Ping Yu, Sai-fu Fung, Shirui Pan, and Guodong Long. 2018 · 2018
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Identifying depression on reddit: The effect of training data
Inna Pirina and Çağrı Çöltekin. 2018 · 2018
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Expert, crowdsourced, and machine assessment of suicide risk via online postings
Han-Chin Shing, Suraj Nair, Ayah Zirikly, Meir Friedenberg, Hal Daumé III, and Philip Resnik. 2018 · 2018
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Publicly Available Clinical BERT Embeddings
Emily Alsentzer, John Murphy, William Boag, Wei-Hung Weng, Di Jindi, Tristan Naumann, and Matthew McDermott. 2019 · 2019
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Ela Gore and Sheetal Rathi. 2019 · 2019
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A BERT-based universal model for both within-and cross-sentence clinical temporal relation extraction
Chen Lin, Timothy Miller, Dmitriy Dligach, Steven Bethard, and Guergana Savova. 2019 · 2019
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BioBERT: a pre-trained biomedical language representation model for biomedical text mining
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MGL-CNN: A hierarchical posts representations model for identifying depressed individuals in online forums
Guozheng Rao, Yue Zhang, Li Zhang, Qing Cong, and Zhiyong Feng. 2020 · 2020
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Automatic detection and classification of cognitive distortions in mental health text
Benjamin Shickel, Scott Siegel, Martin Heesacker, Sherry Benton, and Parisa Rashidi. 2020 · 2020
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Deep learning in mental health outcome research: a scoping review
Chang Su, Zhenxing Xu, Jyotishman Pathak, and Fei Wang. 2020 · 2020
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Fine-Tuning BERT for Multi-Label Sentiment Analysis in Unbalanced Code-Switching Text
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Machine learning in mental health: a scoping review of methods and applications
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Chi Sun, Xipeng Qiu, Yige Xu, and Xuanjing Huang. 2019 · 2019
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Detection of depression-related posts in reddit social media forum
Michael M Tadesse, Hongfei Lin, Bo Xu, and Liang Yang. 2019 · 2019
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Dreaddit: A Reddit Dataset for Stress Analysis in Social Media
Elsbeth Turcan and Kathleen McKeown. 2019 · 2019
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Semantic network analysis for understanding user experiences of bipolar and depressive disorders on reddit
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Application of machine learning methods in mental health detection: a systematic review
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Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A Smith. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Julien Chaumond, Lysandre Debut, Victor Sanh, Clement Delangue, Anthony Moi, Pierric Cistac, Morgan Funtowicz, Joe Davison, Sam Shleifer, et al. 2020 · 2020
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