Sfoglia per Correlatore MISKOVIC, VANJA
Mostrati risultati da 1 a 6 di 6
Benchmarking machine learning models to predict efficacy of immunotherapy in renal and urothelial carcinoma
2023/2024 PICENI, MATTEO
Deep learning-based GTV lesion segmentation and radiomics-driven survival models for NSCLC patients
2024/2025 De Florio, Alessandro
Evaluating LLMs across the scientific research pipeline: a case study on electromagnetic fields as in vitro cancer monotherapy
2025/2026 DENTI, SILVIA
Explainable Machine Learning and Deep Learning models to predict immunotherapy response in NSCLC patients using CT scans
2022/2023 FAVALI, MARGHERITA
Longitudinal machine learning models for CAR-T therapy outcome in large b-cell lymphoma
2024/2025 Simoni, Marco
SHAP-driven explainability in machine learning models applied to urothelial cancer real world data
2023/2024 FERRI, SARA
| Fulltext | Data | Tipo | Titolo | Autore (i) |
|---|---|---|---|---|
| 2023-12-19 | Tesi di laurea Magistrale | Benchmarking machine learning models to predict efficacy of immunotherapy in renal and urothelial carcinoma | PICENI, MATTEO | |
| 2025-04-03 | Tesi di laurea Magistrale | Deep learning-based GTV lesion segmentation and radiomics-driven survival models for NSCLC patients | De Florio, Alessandro | |
| 2026-07-22 | Tesi di laurea Magistrale | Evaluating LLMs across the scientific research pipeline: a case study on electromagnetic fields as in vitro cancer monotherapy | DENTI, SILVIA | |
| 2023-07-18 | Tesi di laurea Magistrale | Explainable Machine Learning and Deep Learning models to predict immunotherapy response in NSCLC patients using CT scans | FAVALI, MARGHERITA | |
| 2026-03-26 | Tesi di laurea Magistrale | Longitudinal machine learning models for CAR-T therapy outcome in large b-cell lymphoma | Simoni, Marco | |
| 2024-12-11 | Tesi di laurea Magistrale | SHAP-driven explainability in machine learning models applied to urothelial cancer real world data | FERRI, SARA |
Mostrati risultati da 1 a 6 di 6
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