Cargando…
External Validation of Robust Radiomic Signature to Predict 2-Year Overall Survival in Non-Small-Cell Lung Cancer
Lung cancer is the second most fatal disease worldwide. In the last few years, radiomics is being explored to develop prediction models for various clinical endpoints in lung cancer. However, the robustness of radiomic features is under question and has been identified as one of the roadblocks in th...
Autores principales: | Jha, Ashish Kumar, Sherkhane, Umeshkumar B., Mthun, Sneha, Jaiswar, Vinay, Purandare, Nilendu, Prabhash, Kumar, Wee, Leonard, Rangarajan, Venkatesh, Dekker, Andre |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10584779/ https://www.ncbi.nlm.nih.gov/pubmed/37735307 http://dx.doi.org/10.1007/s10278-023-00835-8 |
Ejemplares similares
-
Emerging role of quantitative imaging (radiomics) and artificial intelligence in precision oncology
por: Jha, Ashish Kumar, et al.
Publicado: (2023) -
Repeatability and reproducibility study of radiomic features on a phantom and human cohort
por: Jha, A. K., et al.
Publicado: (2021) -
Clinical Concept-Based Radiology Reports Classification Pipeline for Lung Carcinoma
por: Mithun, Sneha, et al.
Publicado: (2023) -
A rare cause of tube arcing artifact seen in computed tomography image of a positron emission tomography/computed tomography scanner
por: Mithun, Sneha, et al.
Publicado: (2016) -
Stair-step artifact seen in coronal and sagittal reformatted images because of misalignment of computed tomography tube, in a positron emission tomography/computed tomography scanner
por: Jha, Ashish Kumar, et al.
Publicado: (2013)