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Predicting radiocephalic arteriovenous fistula success with machine learning

Medicine and Health

Predicting radiocephalic arteriovenous fistula success with machine learning

P. Heindel, T. Dey, et al.

This research presents a breakthrough machine learning tool designed to predict the success of unassisted radiocephalic arteriovenous fistula use, leveraging data from 704 patients. Developed by leading experts including Patrick Heindel and Tanujit Dey, this innovative online calculator integrates key clinical indicators to assist in clinical decision-making.... show more
Citation Metrics
Citations
25
Influential Citations
1
Reference Count
33
Citation by Year

Note: The citation metrics presented here have been sourced from Semantic Scholar and OpenAlex.

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