Cargando…
Challenges in the Use of Artificial Intelligence for Prostate Cancer Diagnosis from Multiparametric Imaging Data
SIMPLE SUMMARY: Prostate Cancer is one of the main threats to men’s health. Its accurate diagnosis is crucial to properly treat patients depending on the cancer’s level of aggressiveness. Tumor risk-stratification is still a challenging task due to the difficulties met during the reading of multi-pa...
Autores principales: | Corradini, Daniele, Brizi, Leonardo, Gaudiano, Caterina, Bianchi, Lorenzo, Marcelli, Emanuela, Golfieri, Rita, Schiavina, Riccardo, Testa, Claudia, Remondini, Daniel |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391234/ https://www.ncbi.nlm.nih.gov/pubmed/34439099 http://dx.doi.org/10.3390/cancers13163944 |
Ejemplares similares
-
Transverse prostate maximum sectional area can predict clinically significant prostate cancer in PI-RADS 3 lesions at multiparametric magnetic resonance imaging
por: Gaudiano, Caterina, et al.
Publicado: (2023) -
Beyond Multiparametric MRI and towards Radiomics to Detect Prostate Cancer: A Machine Learning Model to Predict Clinically Significant Lesions
por: Gaudiano, Caterina, et al.
Publicado: (2022) -
Multiparametric magnetic resonance imaging for the differential diagnosis between granulomatous prostatitis and prostate cancer: a literature review to an intriguing diagnostic challenge
por: Gaudiano, Caterina, et al.
Publicado: (2023) -
Clinical Application of the New Prostate Imaging for Recurrence Reporting (PI-RR) Score Proposed to Evaluate the Local Recurrence of Prostate Cancer after Radical Prostatectomy
por: Ciccarese, Federica, et al.
Publicado: (2022) -
Dynamic FDG PET/CT on bladder paraganglioma: A case report
por: Taninokuchi Tomassoni, Makoto, et al.
Publicado: (2022)