Papers with Predicting
Assessing the Efficacy of Clinical Sentiment Analysis and Topic Extraction in Psychiatric Readmission Risk Prediction (D19-62)
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Elena Alvarez-Mellado, Eben Holderness, Nicholas Miller, Fyonn Dhang, Philip Cawkwell, Kirsten Bolton, James Pustejovsky, Mei-Hua Hall
| Challenge: | Previously, readmission risk classifications rely on structured information, such as sociodemographic data, comorbidity codes and physiological variables. |
| Approach: | They propose to incorporate additional clinically interpretable NLP-based features such as topic extraction and clinical sentiment analysis to predict early readmission risk in psychiatry patients. |
| Outcome: | The proposed model incorporates topic extraction and clinical sentiment analysis to predict early readmission risk in psychiatry patients. |
EgoSpeak: Learning When to Speak for Egocentric Conversational Agents in the Wild (2025.findings-naacl)
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Junhyeok Kim, Min Soo Kim, Jiwan Chung, Jungbin Cho, Jisoo Kim, Sungwoong Kim, Gyeongbo Sim, Youngjae Yu
| Challenge: | EgoSpeak predicts when an agent should begin speaking based on egocentric streaming video. |
| Approach: | They propose a framework for real-time speech initiation prediction in egocentric streaming video by modeling the conversation from the camera wearer's first-person perspective. |
| Outcome: | The proposed framework outperforms random and silence-based baselines in real time and highlights the importance of multimodal input and context length in effectively deciding when to speak. |