Transitional zone prostate cancer: Performance of texture-based machine learning and image-based deep learning

This study is aimed to explore the performance of texture-based machine learning and image-based deep-learning for enhancing detection of Transitional-zone prostate cancer (TZPCa) in the background of benign prostatic hyperplasia (BPH), using a one-to-one correlation between prostatectomy-based path...

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Detalles Bibliográficos
Autores principales: Lee, Myoung Seok, Kim, Young Jae, Moon, Min Hoan, Kim, Kwang Gi, Park, Jeong Hwan, Sung, Chang Kyu, Jeong, Hyeon, Son, Hwancheol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
6800
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545268/
https://www.ncbi.nlm.nih.gov/pubmed/37773806
http://dx.doi.org/10.1097/MD.0000000000035039

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545268/
https://www.ncbi.nlm.nih.gov/pubmed/37773806
http://dx.doi.org/10.1097/MD.0000000000035039

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