PHQ-9
PulseAugur coverage of PHQ-9 — every cluster mentioning PHQ-9 across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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New ePID method offers scalable analysis of symptom network information
Researchers have developed a new method called embedding-based partial information decomposition (ePID) to analyze complex relationships within symptom networks. This technique addresses the computational limitations of…
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LLM-guided concept integration boosts mobile sensing prediction accuracy
Researchers have developed a new model called the Concept-Integrated Transformer (CIT) that uses large language models (LLMs) to improve prediction accuracy and explainability in mobile sensing studies. This approach ge…
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arXiv paper flags criterion contamination in LLM depression evaluations
A new arXiv paper by Tong Li and colleagues argues that "Mirror" evaluations of large language models (LLMs) for depression are contaminated. These evaluations, which use LLM predictions of depression scores based on re…
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New NLP Psychometrics framework evaluates LLM mental health prediction
A new research paper introduces NLP Psychometrics, a framework for evaluating how well Natural Language Processing models predict mental health outcomes. This approach treats text-based psychological prediction as a psy…
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AssemblyAI details AI scribe for therapy notes
AssemblyAI has detailed a method for constructing an AI scribe capable of generating progress notes from therapy sessions. The process involves accurate clinical transcription, distinguishing between the therapist and p…
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New benchmark Psych-ECA evaluates synthetic control arms in psychiatry trials
Researchers have introduced Psych-ECA, a new benchmark designed to evaluate methods for creating synthetic control arms in psychiatric drug development. This benchmark addresses the need for evaluating accuracy, uncerta…
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WPG-MoE framework enhances social media depression detection using LLMs · 2 sources tracked
Researchers have developed WPG-MoE, a novel framework utilizing a large language model (LLM) backbone to improve depression detection from social media data. This system employs a weak-prior-guided dense mixture-of-expe…
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New AI framework enhances multi-dimensional mental health assessment
Researchers have developed PsyBridge, a novel hybrid intelligent framework aimed at improving multi-dimensional mental health assessment. This framework integrates established screening tools like PHQ-9 and GAD-7 with c…
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AI models estimate depression severity from mental health dialogues
Researchers have developed a method to estimate depression severity using conversational data from AI mental health applications. By fine-tuning a Qwen3.5-27B model and augmenting it with pseudolabels generated by Claud…