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Radiogenomics in Renal Cancer Management-Current Evidence and Future Prospects

Articolo
Data di Pubblicazione:
2023
Abstract:
Renal cancer management is challenging from diagnosis to treatment and follow-up. In cases of small renal masses and cystic lesions the differential diagnosis of benign or malignant tissues has potential pitfalls when imaging or even renal biopsy is applied. The recent artificial intelligence, imaging techniques, and genomics advancements have the ability to help clinicians set the stratification risk, treatment selection, follow-up strategy, and prognosis of the disease. The combination of radiomics features and genomics data has achieved good results but is currently limited by the retrospective design and the small number of patients included in clinical trials. The road ahead for radiogenomics is open to new, well-designed prospective studies, with large cohorts of patients required to validate previously obtained results and enter clinical practice.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
artificial intelligence; genomics; machine learning; radiogenomics; radiomics; renal cancer
Elenco autori:
Ferro, Matteo; Musi, Gennaro; Marchioni, Michele; Maggi, Martina; Veccia, Alessandro; Del Giudice, Francesco; Barone, Biagio; Crocetto, Felice; Lasorsa, Francesco; Antonelli, Alessandro; Schips, Luigi; Autorino, Riccardo; Busetto, Gian Maria; Terracciano, Daniela; Lucarelli, Giuseppe; Tataru, Octavian Sabin
Autori di Ateneo:
MARCHIONI MICHELE
Link alla scheda completa:
https://ricerca.unich.it/handle/11564/822936
Pubblicato in:
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Journal
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