PR curves for the Multi-objective Symbolic Regression (MOSR) models: A - Clinical Dataset, B - CFR Dataset, C - Combined CFR and Clinical Dataset.

PR curves for the Multi-objective Symbolic Regression (MOSR) models: A - Clinical Dataset, B - CFR Dataset, C - Combined CFR and Clinical Dataset.

<p>PR curves for the Multi-objective Symbolic Regression (MOSR) models: A - Clinical Dataset, B - CFR Dataset, C - Combined CFR and Clinical Dataset.</p>

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Bibliographic Details
Main Author:	Pietro Arina (10494265) (author)
Other Authors:	Davide Ferrari (163517) (author), Maciej R. Kaczorek (21377347) (author), Nicholas Tetlow (21377350) (author), Amy Dewar (11071829) (author), Robert Stephens (19504) (author), Daniel Martin (279617) (author), Ramani Moonesinghe (13606111) (author), Mervyn Singer (59430) (author), John Whittle (8422482) (author), Evangelos B. Mazomenos (17073049) (author)
Published:	2025
Subjects:	Genetics Science Policy Mental Health Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified several risk scores lack individual precision generate mathematical formulae existing scoring systems demonstrating excellent robustness cardiorespiratory fitness derived cardiopulmonary exercise testing assessing perioperative risks analyze feature contributions postoperative day 3 pinpoint essential features predict patient morbidity elective surgical patients 1190 elderly patients predicting postoperative morbidity postoperative morbidity survey cpet ), demographic cardiorespiratory fitness models mosr model surpassed mosr model stands advanced machine learning mosr ), postoperative morbidity machine learning cpet time clinical features learning tasks underlying models subsequently used sole reliance poms ). local institution great value generalization capabilities every experiment data input clinical teams clinical data build models analyzed retrospectively address limitations
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