Wilms tumor response to chemotherapy, Oncology.
| Article DOI | https://doi.org/10.3390/diagnostics13030486 |
| Objective | To assess the response of Wilms’ tumors to preoperative chemotherapy |
| AI Approach | Support vector machines |
| Data Source(s) | Single institutional series (63 patients) |
| Model Input | Regions of interest from CT images (incl. Shape features, functionality-based features, appearance features) |
| Model Outcome | Prediction of tumor response to neoadjuvant chemotherapy |
| Model Metrics | Accuracy of 95%, Sensitivity of 96% Specificity of 94%, F1-score of 0.97 |
| Model Usability | NA |
AI = Artificial intelligence, SFU = Society for Fetal Urology, CNN = Convolutional Neural Network
AIPEDURO 
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