Table 2_Baseline indices of cardiorespiratory fitness for predicting acute mountain sickness: an interpretable four-task ensemble model.docx

The area under the receiver operating characteristic curve and decision curve analysis were evaluated to calculate predictive power and assess the model’s clinical applicability.</p>Results<p>Following algorithm comparison, AMS-FTE model was constructed to provide unified predictions for the four AMS-related tasks. Based on feature importance rankings, interpretable final model was developed for each task using the top 5 contributing features, which were associated with baseline cardiopulmonary fitness (post-exercise heart rate, post-exercise SpO₂, AT-RCP time, peak VO₂, and ΔVO₂ AT-RCP).

This model demonstrated robust predictive accuracy for AMS, and showed significant clinical net benefit probability ranges, demonstrating strong clinical applicability.</p>Conclusion<p>The predictive value of baseline cardiorespiratory fitness parameters proved valuable in distinguishing AMS and non-AMS subjects, as revealed through an interpretable ML model and a support system. This will enable earlier diagnosis for AMS, and more targeted interventions for acute altitude illness.</p>