从叙事到数字：利用语言模型对口头尸检叙事的预测进行有效推断

Using Machine Learning to Fuse Verbal Autopsy Narratives and Binary Features in the Analysis of Deaths from Hyperglycaemia

Lower-and-middle income countries are faced with challenges arising from a lack of data on cause of death (COD), which can limit decisions on population health and disease management. A verbal autopsy(VA) can provide information about a COD in areas without robust death registration systems. A VA consists of structured data, combining numeric and binary features, and unstructured data as part of an open-ended narrative text. This study assesses the performance of various machine learning approaches when analyzing both the structured and unstructured components of the VA report. The algorithms …

A Comparative Study of Machine Learning Methods for Verbal Autopsy Text Classification

A Verbal Autopsy is the record of an interview about the circumstances of an uncertified death. In developing countries, if a death occurs away from health facilities, a field-worker interviews a relative of the deceased about the circumstances of the death; this Verbal Autopsy can be reviewed off-site. We report on a comparative study of the processes involved in Text Classification applied to classifying Cause of Death: feature value representation; machine learning classification algorithms; and feature reduction strategies in order to identify the suitable approaches applicable to the clas…

LAVA：语言模型辅助的口头尸检用于死因判定

LAVA: Language Model Assisted Verbal Autopsy for Cause-of-Death Determination

本研究提出LA-VA流程，结合大型语言模型与传统算法及嵌入分类，在PHMRC数据集上显著提升口头尸检死因预测准确率，GPT-5表现最佳，较传统基线提高5-10%。

Improving Cause-of-Death Classification from Verbal Autopsy Reports

In many lower-and-middle income countries including South Africa, data access in health facilities is restricted due to patient privacy and confidentiality policies. Further, since clinical data is unique to individual institutions and laboratories, there are insufficient data annotation standards and conventions. As a result of the scarcity of textual data, natural language processing (NLP) techniques have fared poorly in the health sector. A cause of death (COD) is often determined by a verbal autopsy (VA) report in places without reliable death registration systems. A non-clinician field wo…

在口头尸检分析中利用语言模型和机器学习

Leveraging Language Models and Machine Learning in Verbal Autopsy Analysis

本研究利用预训练语言模型与机器学习处理口头尸检叙述，证明其可提升死亡原因分类，并通过多模态融合与信息充分性分析为VA工具改进提供依据。

MBTI Personality Prediction for Fictional Characters Using Movie Scripts

An NLP model that understands stories should be able to understand the characters in them. To support the development of neural models for this purpose, we construct a benchmark, Story2Personality. The task is to predict a movie character's MBTI or Big 5 personality types based on the narratives of the character. Experiments show that our task is challenging for the existing text classification models, as none is able to largely outperform random guesses. We further proposed a multi-view model for personality prediction using both verbal and non-verbal descriptions, which gives improvement com…