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Primary health conditions among medical crowdfunding campaigns in the US: A Natural Language Processing Approach
Shaojun Yu;
Shu Liu;
K. Robin Yabroff;
Farhad Islami;
Fumiko Chino;
Jing Zhang;
Zhiyuan Zheng
ABSTRACT
In a contemporary analysis of more than 122,000 U.S. medical crowdfunding campaigns, we used an empirical NLP model to identify the 20 most common disease categories; these campaigns collectively raised approximately $531.6 million per year. Cancer accounted for the largest share, followed by injury-related and cardiovascular conditions. Only 9.2% of campaigns met their fundraising goals within 90 days of launch, with substantial variation across conditions—underscoring patient vulnerability and the limitations of U.S. insurance coverage and social safety nets.
Citation
Please cite as:
Yu S, Liu S, Yabroff KR, Islami F, Chino F, Zhang J, Zheng Z
Primary Health Conditions Among Medical Crowdfunding Campaigns in the United States: Natural Language Processing Study