Leveraging Large Language Models and Machine Learning for Success Analysis in Robust Cancer Crowdfunding Predictions: Quantitative Study

Abstract

This study demonstrates that LLMs such as GPT-4o can effectively extract nuanced linguistic and social features from crowdfunding narratives, offering deeper insights than traditional methods. These features, when combined with machine learning, significantly improve the identification of key predictors of campaign success, such as medical severity, financial hardship, and empathetic communication. Our findings underscore the potential of LLMs to enhance predictive modeling in health-related crowdfunding and support more targeted policy and communication strategies to reduce financial vulnerability among patients with cancer.

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