Raw performance metrics for the MLP model.

<p>The table presents the raw output from the bootstrap analysis, showing the mean, lower, and upper confidence interval bounds for the AUC of local and federated models, and the performance gain (<i>Δ</i>AUC). It provides a hospital-level breakdown of the mean AUC and 95% CI for t...

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সংরক্ষণ করুন:

গ্রন্থ-পঞ্জীর বিবরন
প্রধান লেখক:	Roberta Moreira Wichmann (14259316) (author)
অন্যান্য লেখক:	Murilo Afonso Robiati Bigoto (22676715) (author), Alexandre Dias Porto Chiavegatto Filho (14259328) (author)
প্রকাশিত:	2025
বিষয়গুলি:	Cell Biology Ecology Cancer Science Policy Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified via parameter aggregation using ensemble aggregation strong inverse correlation maximum performance degradation benefits requires caution beneficial collaborative effect >&# 916 ;</ 19 mortality using 19 mortality prediction local patient volume statistically certain benefits statistical significance showed 0273 ]) due auc crossed zero study validates fl fl models demonstrated performance gain (< evaluated federated learning div >< p collaborative model ’ auc minus auc local data scarcity ci [– 0 gain ’ federated learning local validation universally certain statistical advantage 6307 ]) auc across – 0 volatile algorithm smallest hospital particularly evident network (< multicentric sample multicenter sample limited institutions layer perceptron iid ). high sensitivity findings underscore every site enabling mechanism despite achieving confidence intervals 500 ). 022 patients
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Raw performance metrics for the MLP model.

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