Orchiectomy in torsion, Testicular torsion.
| Article DOI | https://doi.org/10.1007/s00383-022-05185-0 |
| Objective | To predict the likelihood of orchiectomy rather than orchiopexy in testicular torsion using preoperative features |
| AI Approach | Random forrest |
| Data Source(s) | Single institutional series (256 children in the development set, 44 children in the testing set) |
| Model Input | 26 parameters from clinical findings and US, including demographic data (age, body mass index), presentation (symptom duration, chief complaint), laboratory investigations, Imaging data from Doppler ultrasound, time and location of presentation |
| Model Outcome | Orchiectomy |
| Model Metrics | AUC 0.95 Sensitivity 0.92 Specificity 0.89 |
| Model Usability | NA |
AI = Artificial intelligence
AIPEDURO 
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