Deep Representations of First-person Pronouns for Prediction of Depression Symptom Severity
University of Washington（华盛顿大学）；Talkspace
Xinyang Ren, Hannah A Burkhardt, Patricia A Areán, Thomas D Hull, Trevor Cohen
备注：
Accepted: AMIA Annual Symposium 2023. To appear as: Ren X, Burkhardt H, Areán P, Hull T, Cohen T. Deep Representations of First-person Pronouns for Prediction of Depression Symptom Severity. AMIA Annual Symposium Proceedings 2023. American Medical Informatics Association
Prior work has shown that analyzing the use of first-person singular pronouns can provide insight into individuals' mental status, especially depression symptom severity. These findings were generated by counting frequencies of first-person singular pronouns in text data. However, counting doesn't capture how these pronouns are used. Recent advances in neural language modeling have leveraged methods generating contextual embeddings. In this study, we sought to utilize the embeddings of first-person pronouns obtained from contextualized language representation models to capture ways these pronouns are used, to analyze mental status. De-identified text messages sent during online psychotherapy with weekly assessment of depression severity were used for evaluation. Results indicate the advantage of contextualized first-person pronoun embeddings over standard classification token embeddings and frequency-based pronoun analysis results in predicting depression symptom severity. This suggests contextual representations of first-person pronouns can enhance the predictive utility of language used by people with depression symptoms.
Evaluating Lexicon Incorporation for Depression Symptom Estimation
Normandie Univ, UNICAEN, ENSICAEN, CNRS, GREYC（诺曼底大学、卡昂大学、卡昂高等工程师学院、法国国家科学研究中心、格雷西研究所）；Institute of Computer Science, University of Tartu（塔尔图大学计算机科学研究所）
Interpretable Symptom Vectors for Depression in a Large Language Model
Stanford University School of Medicine（斯坦福大学医学院）；Wu Tsai Neurosciences Institute, Stanford University（斯坦福大学吴蔡神经科学研究所）；Kaiser Permanente（凯撒医疗机构）；BigCommerce（BigCommerce公司）；Veterans Affairs Palo Alto Healthcare System（帕洛阿尔托退伍军人事务医疗系统）；Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC)（塞拉太平洋精神疾病研究、教育和临床中心（MIRECC））
Optimizing Large Language Models for Detecting Symptoms of Comorbid Depression or Anxiety in Chronic Diseases: Insights from Patient Messages
Stanford University（斯坦福大学）；Stanford School of Medicine（斯坦福医学院）；Stanford Health Care（斯坦福医疗保健系统）；Google LLC（谷歌公司）；Beth Israel Deaconess Medical Center（贝斯以色列女执事医疗中心）；Veterans Affairs Palo Alto Health Care System（帕洛阿尔托退伍军人事务医疗保健系统）
Candidate Generation and Definition-Guided Verification for Sentence-Level Depression Symptom Recognition
Institute for Systems and Robotics (ISR)（系统与机器人研究所）；Instituto Superior Técnico (IST)（高等技术学院）；University of Lisbon（里斯本大学）；Hospital Beatriz Ângelo（Beatriz Ângelo医院）
Explaining GPTs' Schema of Depression: A Machine Behavior Analysis
Stony Brook University（石溪大学）；Carnegie Mellon University（卡内基梅隆大学）；Lund University（吕勒欧大学）；Stanford University（斯坦福大学）；Institute of Human-Centered AI at Stanford University（斯坦福大学人机交互人工智能研究所）；The University of Texas at Dallas（德克萨斯大学达拉斯分校）；Vanderbilt University（范德比大学）；University of Bonn（波恩大学）；The Lamarr Institute for Machine Learning & Artificial Intelligence（拉马尔人工智能与机器学习研究所）
Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires
University of Amsterdam（阿姆斯特丹大学）；Max Planck Institute for Informatics（马克斯·普朗克信息学研究所）；Johns Hopkins University（约翰斯·霍普金斯大学）；National Institutes of Health（美国国立卫生研究院）；Allen Institute for AI（艾伦人工智能研究所）
Semantic Similarity Models for Depression Severity Estimation
Centro de Investigación en Tecnoloxías da Información e as Comunicacións (CITIC)（信息与通信技术研究中心（CITIC））；Universidade da Coruña（拉科鲁尼亚大学）；Hessian Center for AI (hessian.AI)（黑森人工智能中心（hessian.AI））；Technical University of Darmstadt（达姆施塔特工业大学）
Data-driven Approach to Differentiating between Depression and Dementia from Noisy Speech and Language Data
Winterlight Labs（Winterlight实验室）；University of Toronto（多伦多大学）；Vector Institute for Artificial Intelligence（Vector人工智能研究所）；Li Ka Shing Knowledge Institute（李嘉诚知识研究院）；St Michael’s Hospital（圣迈克尔医院）；Surgical Safety Technologies Inc.（手术安全技术公司）
Psychologically-Grounded Graph Modeling for Interpretable Depression Detection
Singapore Institute of Technology（新加坡科技学院）；Nanyang Technological University（南洋理工大学）；ELLIS Institute Finland（芬兰ELLIS研究所）；University of Turku（图尔库大学）；Princess Nourah bint Abdulrahman University（普里西拉努拉·本·阿卜杜勒拉赫曼大学）
Multilingual Lexical Feature Analysis of Spoken Language for Predicting Major Depression Symptom Severity
University of Sussex（萨塞克斯大学）；Sant Joan de Déu Research Institut（圣琼德德乌研究所）；Mental Health Networking Biomedical Research Centre (CIBERSAM)（精神健康网络生物医学研究中心（CIBERSAM））；Amsterdam University Medical Centre, Vrije Universiteit（阿姆斯特丹自由大学阿姆斯特丹大学医学中心）；South London and Maudsley NHS Foundation Trust（南伦敦和莫兹利国民保健服务基金会信托）；University of Zaragoza（萨拉戈萨大学）；Biomedical Research Networking Centre in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN)（生物工程、生物材料与纳米医学生物医学研究网络中心（CIBER-BBN））；Janssen Research and Development LLC（杨森研发有限责任公司）；University College London（伦敦大学学院）；Davos Alzheimer's Collaborative（达沃斯阿尔茨海默病协作组织）
Identifying Depressive Symptoms from Tweets: Figurative Language Enabled Multitask Learning Framework
LHNCBC, U.S. National Library of Medicine（美国国家医学图书馆 LHNCBC）；Indian Institute of Technology Gandhinagar（印度理工学院甘地讷格尔分校）；Wright State University（莱特州立大学）；University of South Carolina（南卡罗来纳大学）
Depression Detection on Social Media with Large Language Models
Department of Electronic Engineering, BNRist, Tsinghua University（电子工程系，北京理工大学，清华大学）；College of Computing and Data Science, Nanyang Technological University（计算与数据科学学院，南洋理工大学）；Department of Computer Science, The University of Chicago（计算机科学系，芝加哥大学）
The Expressions of Depression and Anxiety in Chinese Psycho-counseling: Usage of First-person Singular Pronoun and Negative Emotional Words
Hangzhou Normal University（杭州师范大学）；Zhejiang University（浙江大学）；Westlake University（西湖大学）；Queen Mary University of London（伦敦玛丽女王大学）；Hangzhou Polytechnic（杭州职业技术学院）
Enhancing Depression Detection with Chain-of-Thought Prompting: From Emotion to Reasoning Using Large Language Models
College of Information Science and Engineering, Ritsumeikan University（立命馆大学信息科学与工程学院）；Fujita Health University（藤田医科大学）；College of Computer Science and Technology, Zhejiang University（浙江大学计算机科学与技术学院）
DS@GT at eRisk 2025: From prompts to predictions, benchmarking early depression detection with conversational agent based assessments and temporal attention models
Language-Agnostic Analysis of Speech Depression Detection
Saintgits College of Engineering（圣吉茨工程学院）；IIIT Hyderabad（印度信息技术研究所海得拉巴分校）；Cognitive Science Lab, IIIT Hyderabad（印度信息技术研究所海得拉巴分校认知科学实验室）；Language Technologies Research Center, IIIT Hyderabad（印度信息技术研究所海得拉巴分校语言技术研究中心）
From Detection to Discovery: A Closed-Loop Approach for Simultaneous and Continuous Medical Knowledge Expansion and Depression Detection on Social Media
Shenzhen University（深圳大学）；Iowa State University（爱荷华州立大学）；University of Delaware（特拉华大学）；University of Arizona（亚利桑那大学）
DS@GT eRisk 2024: Sentence Transformers for Social Media Risk Assessment
Georgia Institute of Technology（佐治亚理工学院）；Peoples' Friendship University of Russia (RUDN University)（俄罗斯人民友谊大学（RUDN大学））；Joint Institute for Nuclear Research（联合核研究所）；Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）；University of Skövde（舍夫德大学）
Streamlining Social Media Information Retrieval for COVID-19 Research with Deep Learning
Harvard Chan School of Public Health（哈佛陈曾熙公共卫生学院）；Harvard Medical School（哈佛医学院）；Brigham and Women’s Hospital（布列根和妇女医院）；Zhejiang University School of Medicine（浙江大学医学院）；The Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））
