Two new research papers explore advanced AI techniques for detecting opioid craving and stress. The first paper, RETRACE, uses a resilience-guided, trait-conditioned framework with wearable physiological data to improve subject-independent craving estimation. The second paper, FABLE-Therm, utilizes contactless thermal video to sense stress and craving, demonstrating that localized thermal evidence is crucial and that representation alone is insufficient for equitable deployment. AI
IMPACT These studies advance AI's role in mental health by developing new methods for detecting stress and craving, potentially leading to more proactive interventions for opioid use disorder.
RANK_REASON Two academic papers published on arXiv detailing novel AI models for detecting opioid craving and stress.
- alphaXiv
- arXiv
- CatalyzeX
- Connected Papers
- DagsHub
- FABLE-Therm
- Gotit.pub
- Hugging Face
- Litmaps
- opioid use disorder
- RETRACE
- ScienceCast
- scite Smart Citations
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