A5074138666- Topic Modeling
- Natural Language Processing Techniques
- Mental Health via Writing
- Digital Mental Health Interventions
- Biomedical Text Mining and Ontologies
- Machine Learning in Healthcare
- Health Literacy and Information Accessibility
- Chronic Disease Management Strategies
- Sentiment Analysis and Opinion Mining
- Mental Health Research Topics
- Interpreting and Communication in Healthcare
- Text and Document Classification Technologies
- Suicide and Self-Harm Studies
- Speech and dialogue systems
- Nursing Diagnosis and Documentation
- Data Quality and Management
- Health disparities and outcomes
- Semantic Web and Ontologies
- Food Security and Health in Diverse Populations
- Impact of Technology on Adolescents
- Authorship Attribution and Profiling
- Misinformation and Its Impacts
- Healthcare Policy and Management
- AI in cancer detection
- Autopsy Techniques and Outcomes
Johns Hopkins University
2022-2025
National Institutes of Health Clinical Center
2018-2023
Tufts University
2022
University of Pittsburgh
2022
University of Maryland, Baltimore
2022
Harvard University
2022
University of Southern California
2022
Ellipsis
2022
National Institutes of Health
2018-2019
Stanford University
2018
Han-Chin Shing, Suraj Nair, Ayah Zirikly, Meir Friedenberg, Hal Daumé III, Philip Resnik. Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic. 2018.
The shared task for the 2019 Workshop on Computational Linguistics and Clinical Psychology (CLPsych’19) introduced an assessment of suicide risk based social media postings, using data from Reddit to identify users at no, low, moderate, or severe risk. Two variations focused whose posts r/SuicideWatch subreddit indicated they might be risk; a third looked screening only their more everyday (non-SuicideWatch) posts. We received submissions 15 different teams, results provide progress insight...
Automated methods have been widely used to identify and analyze mental health conditions (e.g., depression) from various sources of information, including social media. Yet, deployment such models in real-world healthcare applications faces challenges poor out-of-domain generalization lack trust black box models. In this work, we propose approaches for depression detection that are constrained different degrees by the presence symptoms described PHQ9, a questionnaire clinicians screening...
The majority of research on Arabic Named Entity Recognition (NER) addresses the task for newswire genre, where language used is Modern Standard (MSA), however, need to study this in social media becoming more vital. Social characterized by use both MSA and Dialectal (DA), with often code switching between two varieties. Despite some common characteristics DA, there are significant differences which result poor performance when targeting systems applied NER DA. Additionally, most rely...
Adam Tsakalidis, Jenny Chim, Iman Munire Bilal, Ayah Zirikly, Dana Atzil-Slonim, Federico Nanni, Philip Resnik, Manas Gaur, Kaushik Roy, Becky Inkster, Jeff Leintz, Maria Liakata. Proceedings of the Eighth Workshop on Computational Linguistics and Clinical Psychology. 2022.
Mood and anxiety disorders are prevalent mental health diagnoses. Numerous studies have shown that measurement-based care, which is used to monitor patient symptoms, functioning, treatment progress help guide clinical decisions collaboration on goals, can improve outcomes in patients with these disorders. Including digital information regarding patients' electronic communications social media activity an innovative approach augmenting care. Recent data indicate interest willingness from both...
YouthLine developed Safe Social Spaces (SSS), a program that trains young adult crisis specialists to identify and assist youths expressing suicidal thoughts behaviors on social media platforms. Crisis contacted 3868 in from across the United States through private messaging 2019 2024. Fifty-six percent of responded outreach by SSS. SSS is scalable program, created meet where they are—on online. ( Am J Public Health. 2025;115(4):473–476. https://doi.org/10.2105/AJPH.2024.307970 )
<sec> <title>BACKGROUND</title> Digital social activity, defined as interactions on media and electronic communication platforms, has become increasingly important. Social factors impact mental health can contribute to depression anxiety. Therefore, incorporating digital activity into routine care the potential improve outcomes. </sec> <title>OBJECTIVE</title> To compare treatment augmented with an dashboard of patient's versus treatment-as-usual patient-rated outcomes symptoms in a...
Sean MacAvaney, Bart Desmet, Arman Cohan, Luca Soldaini, Andrew Yates, Ayah Zirikly, Nazli Goharian. Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic. 2018.
Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have surged in popularity recent years, with discussions about their on-label and off-label use spilling into the public forum. No study has analyzed online GLP-1RAs.
Ayah Zirikly, Masato Hagiwara. Proceedings of the 53rd Annual Meeting Association for Computational Linguistics and 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). 2015.
Abstract Background Human activity and the interaction between health conditions is a critical part of understanding overall function individuals. The World Health Organization’s International Classification Functioning, Disability (ICF) models as all aspects an individual’s with world, including organismal concepts such individual body structures, functions, pathologies, well outcomes their environment, referred to participation. Function, particularly participation outcomes, important...
Functioning is gaining recognition as an important indicator of global health, but remains under-studied in medical natural language processing research. We present the first analysis automatically extracting descriptions patient mobility, using a recently-developed dataset free text electronic health records. frame task named entity (NER) problem, and investigate applicability NER techniques to mobility extraction. As corpora focused on functioning are scarce, we explore domain adaptation...
Abstract Objectives Normalizing mentions of medical concepts to standardized vocabularies is a fundamental component clinical text analysis. Ambiguity—words or phrases that may refer different concepts—has been extensively researched as part information extraction from biomedical literature, but less known about the types and frequency ambiguity in text. This study characterizes distribution distinct exhibited by benchmark concept normalization datasets, order identify directions for...
Natural language processing (NLP) in health care enables transformation of complex narrative information into high value products such as clinical decision support and adverse event monitoring real time via the electronic record (EHR). However, technologies for mental have consistently lagged because complexity measuring modeling illness. The use NLP to management conditions is a viable topic that has not been explored depth. This paper provides framework advanced application methods...
Keith Harrigian, Ayah Zirikly, Brant Chee, Alya Ahmad, Anne Links, Somnath Saha, Mary Catherine Beach, Mark Dredze. Proceedings of the 61st Annual Meeting Association for Computational Linguistics (Volume 2: Short Papers). 2023.
Abstract Objectives To develop and test a scalable, performant, rule-based model for identifying 3 major domains of social needs (residential instability, food insecurity, transportation issues) from the unstructured data in electronic health records (EHRs). Materials Methods We included patients aged 18 years or older who received care at Johns Hopkins Health System (JHHS) between July 2016 June 2021 had least 1 (free-text) note their EHR during study period. used combination manual lexicon...
Secondary use of Electronic Health Records (EHRs) has mostly focused on health conditions (diseases and drugs). Function is an important indicator in addition to morbidity mortality. Nevertheless, function been overlooked accessing patients' status. The World Organization (WHO)'s International Classification Functioning, Disability (ICF) considered the international standard for describing coding states. We pioneer first comprehensive analysis identification functioning concepts Mobility domain ICF.
Models of mental health based on natural language processing can uncover latent signals from language. that indicate whether an individual is depressed, or has other conditions, aid in diagnosis and treatment. A critical aspect integration these models into the clinical setting relies explaining their behavior to domain experts. In case diagnosis, clinicians already rely assessment framework make decisions; help a model generate meaningful explanations.In this work we propose use PHQ-9...
<sec> <title>BACKGROUND</title> Mood and anxiety disorders are prevalent mental health diagnoses. Numerous studies have shown that measurement-based care, which is used to monitor patient symptoms, functioning, treatment progress help guide clinical decisions collaboration on goals, can improve outcomes in patients with these disorders. Including digital information regarding patients’ electronic communications social media activity an innovative approach augmenting care. Recent data...