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Limited access to mental healthcare resources hinders timely depression diagnosis, leading to detrimental outcomes.
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Studying the amateur artist: A perspective on disguising data collected in human subjects research on the internet
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Development and natural history of mood disorders
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Nicolas Rüsch, Matthias C Angermeyer, and Patrick W Corrigan · 2005
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The relationship between precision-recall and roc curves
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Karen D Rudolph, Constance Hammen, and Shannon E Daley · 2006
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Darrel A Regier, Emily A Kuhl, and David J Kupfer · 2013
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Quantifying mental health signals in twitter
Glen Coppersmith, Mark Dredze, and Craig Harman · 2014
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Xgboost: A scalable tree boosting system
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Data-driven classification of bipolar i disorder from longitudinal course of mood
AL Cochran, MG McInnis, and DB Forger · 2016
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Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Hérve Jégou, and Tomas Mikolov · 2016
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Economic burden of mental illnesses in pakistan
Murad Moosa Khan et al · 2016
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A test collection for research on depression and language use
David E Losada and Fabio Crestani · 2016
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Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy · 2016
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A qualitative study examining experiences and dilemmas in concealment and disclosure of people living with serious mental illness
Shani Bril-Barniv, Galia S Moran, Adi Naaman, David Roe, and Orit Karnieli-Miller · 2017
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Longitudinal cognitive trajectories and associated clinical variables in youth with bipolar disorder
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# mydepressionlookslike: Examining public discourse about depression on twitter
E Megan Lachmar, Andrea K Wittenborn, Katherine W Bogen, and Heather L McCauley · 2017
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Depression detection via harvesting social media: A multimodal dictionary learning solution
Guangyao Shen, Jia Jia, Liqiang Nie, Fuli Feng, Cunjun Zhang, Tianrui Hu, Tat-Seng Chua, Wenwu Zhu, et al · 2017
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Early identification of depression severity levels on reddit using ordinal classification
Usman Naseem, Adam G Dunn, Jinman Kim, and Matloob Khushi · 2022
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A mental state knowledge–aware and contrastive network for early stress and depression detection on social media
Kailai Yang, Tianlin Zhang, and Sophia Ananiadou · 2022
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Natural language processing applied to mental illness detection: a narrative review
Tianlin Zhang, Annika M Schoene, Shaoxiong Ji, and Sophia Ananiadou · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Depression detection on online social network with multivariate time series feature of user depressive symptoms
Yicheng Cai, Haizhou Wang, Huali Ye, Yanwen Jin, and Wei Gao · 2023
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Facebook language predicts depression in medical records
Johannes C Eichstaedt, Robert J Smith, Raina M Merchant, Lyle H Ungar, Patrick Crutchley, Daniel Preoţiuc-Pietro, David A Asch, and H Andrew Schwartz · 2018
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Hierarchical neural model with attention mechanisms for the classification of social media text related to mental health
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Deep learning for depression detection of twitter users
Ahmed Husseini Orabi, Prasadith Buddhitha, Mahmoud Husseini Orabi, and Diana Inkpen · 2018
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Early detection of depression: social network analysis and random forest techniques
Fidel Cacheda, Diego Fernandez, Francisco J Novoa, and Victor Carneiro · 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
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Sensemood: depression detection on social media
Chenhao Lin, Pengwei Hu, Hui Su, Shaochun Li, Jing Mei, Jie Zhou, and Henry Leung · 2020
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Domain-specific continued pretraining of language models for capturing long context in mental health
Shaoxiong Ji, Tianlin Zhang, Kailai Yang, Sophia Ananiadou, Erik Cambria, and Jörg Tiedemann · 2023
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Large language models encode clinical knowledge
Karan Singhal, Shekoofeh Azizi, Tao Tu, S Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, et al · 2023
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Exploring social media for early detection of depression in covid-19 patients
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Towards interpretable mental health analysis with large language models
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Mentalllama: Interpretable mental health analysis on social media with large language models
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Phq-aware depressive symptoms identification with similarity contrastive learning on social media
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Sentiment-guided transformer with severity-aware contrastive learning for depression detection on social media
Tianlin Zhang, Kailai Yang, and Sophia Ananiadou · 2023
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Can large language models transform computational social science?
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An assessment on comprehending mental health through large language models
Mihael Arcan, Paul-David Niland, and Fionn Delahunty · 2024
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Large language models in mental health care: a scoping review
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