Cuestionario vinculado a una guía · Medio Nivel
IA en el cuestionario de predicción de lesiones de los deportistas
Revise las características de la carga de trabajo, los estudios de lesiones basados en GPS, el desequilibrio de clases, los límites de validación, las métricas del modelo y la incertidumbre en las estimaciones del riesgo de lesiones.
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What does the acute-to-chronic workload ratio summarize?
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Las respuestas y explicaciones aparecen a medida que realiza el cuestionario.
- What does the acute-to-chronic workload ratio summarize?
- A recent workload relative to a longer-term workload summary
- A player’s injury severity relative to salary
- A team’s travel time relative to match time
- Heart-rate variability relative to sleep duration
- Why can injury models be difficult to evaluate when the outcome is uncommon?
- Every athlete has the same outcome
- A model can appear accurate while missing many rare injury events
- Rare events eliminate the need for validation
- A high accuracy score guarantees useful prediction
- Which measurements did the Australian football workload study use?
- Ticket scans and social-media posts
- Only heart-rate variability
- GPS, accelerometer, and player-perceived exertion data
- Only video of match officials
- What does an injury-forecasting model estimate?
- A guaranteed date of injury
- A clinical diagnosis without examination
- A certain training prescription
- A probability or risk estimate for a defined outcome and period
- What did Carey et al. report for non-contact injury prediction on the later season?
- Performance was only marginally better than chance, with AUC below 0.65
- Every outcome had perfect accuracy
- AUC was always 1.0
- The study did not test a later season
- What validation gap did the 2026 systematic review report for all included studies?
- All used a separate country for testing
- None used external validation
- All models were tested prospectively in clinics
- No study reported any outcome metrics
- Which split did the Australian football study use to test its injury forecasts?
- It mixed all three seasons randomly for every result
- It trained only on injury labels from the third season
- It trained using the first two seasons and evaluated predictions on the third
- It evaluated only on the training rows
- What do sensitivity and specificity measure in an injury model?
- They both measure only training speed
- Sensitivity is cost and specificity is model size
- They are alternative names for data leakage
- Sensitivity concerns detecting injured cases; specificity concerns correctly identifying non-injured cases