Zobrazeno 1 - 10
of 537
pro vyhledávání: '"radiomic features"'
Autor:
Rania M. Mohamed, Bikash Panthi, Beatriz E. Adrada, Medine Boge, Rosalind P. Candelaria, Huiqin Chen, Mary S. Guirguis, Kelly K. Hunt, Lei Huo, Ken-Pin Hwang, Anil Korkut, Jennifer K. Litton, Tanya W. Moseley, Sanaz Pashapoor, Miral M. Patel, Brandy Reed, Marion E. Scoggins, Jong Bum Son, Alastair Thompson, Debu Tripathy, Vicente Valero, Peng Wei, Jason White, Gary J. Whitman, Zhan Xu, Wei Yang, Clinton Yam, Jingfei Ma, Gaiane M. Rauch
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Triple-negative breast cancer (TNBC) is often treated with neoadjuvant systemic therapy (NAST). We investigated if radiomic models based on multiparametric Magnetic Resonance Imaging (MRI) obtained early during NAST predict pathologic comple
Externí odkaz:
https://doaj.org/article/6a9d5085faa94e07a2d7d1b1c2688f40
Publikováno v:
Frontiers in Microbiology, Vol 15 (2024)
ObjectiveBy extracting early chest CT radiomic features of COVID-19 patients, we explored their correlation with laboratory indicators and oxygenation index (PaO2/FiO2), thereby developed an Artificial Intelligence (AI) model based on radiomic featur
Externí odkaz:
https://doaj.org/article/033a5a9baddf439cade5005ba87c02e2
Publikováno v:
Cancer Medicine, Vol 13, Iss 20, Pp n/a-n/a (2024)
ABSTRACT Objective Lung cancer remains the leading cause of cancer‐related mortality worldwide, with most cases diagnosed at advanced stages. Hence, there is a need to develop effective predictive models for early detection. This study aims to inve
Externí odkaz:
https://doaj.org/article/30638309cfd540339fba3bd91d3e3544
Autor:
Anna Corti, Stefano Cavalieri, Giuseppina Calareso, Davide Mattavelli, Marco Ravanelli, Tito Poli, Lisa Licitra, Valentina D. A. Corino, Luca Mainardi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract The clinical applicability of radiomics in oncology depends on its transferability to real-world settings. However, the absence of standardized radiomics pipelines combined with methodological variability and insufficient reporting may hampe
Externí odkaz:
https://doaj.org/article/7c52f0e8a5ff4752a75df55bcb9199f2
Autor:
A. M. H. H. Alahakoon, C. K. Walgampaya, Shyama Walgampaya, I. U. Ekanayake, Janaka Alawatugoda
Publikováno v:
IEEE Access, Vol 12, Pp 145234-145253 (2024)
Glioblastoma multiforme (GBM) is a WHO grade IV tumor and its heterogeneity pushes oncologists to focus on more personalized treatments for individual patients. This challenge is aided by radiomics, which involves the extraction of valuable features
Externí odkaz:
https://doaj.org/article/475a26e6c1da480996d1ed23e5715549
Publikováno v:
IEEE Access, Vol 12, Pp 18295-18314 (2024)
Cardiac pathology classification (CPC) based on the volumetric features of three key heart structures can be extracted from segmented cardiac cine magnetic resonance imaging (CMRI) sequences. Machine learning models have recently become very effectiv
Externí odkaz:
https://doaj.org/article/f864b1b4ce9543fbbee876c88f245b4f
Autor:
Dewa Putu Wisnu Wardhana, Sri Maliawan, Tjokorda Gde Bagus Mahadewa, Rohadi Muhammad Rosyidi, Sinta Wiranata
Publikováno v:
Diagnostics, Vol 14, Iss 21, p 2354 (2024)
Background: Glioblastoma, the predominant primary tumor among all central nervous systems, accounts for around 80% of cases. Prognosis in neuro-oncology involves assessing the disease’s progression in different individuals, considering the time bet
Externí odkaz:
https://doaj.org/article/51e6da6dfb89432ba781ff4e3319c782
Publikováno v:
BMC Medical Imaging, Vol 23, Iss 1, Pp 1-10 (2023)
Abstract Background Lymph node metastasis is an important factor affecting the treatment and prognosis of patients with cervical cancer. However, the comparison of different algorithms and features to predict lymph node metastasis is not well underst
Externí odkaz:
https://doaj.org/article/bf08e40359c947d1a2f054f5c5e556c6
Publikováno v:
F1000Research, Vol 13 (2024)
Background Breast cancer (BC) is one of the main causes of cancer-related mortality among women. For clinical management to help patients survive longer and spend less time on treatment, early and precise cancer identification and differentiation of
Externí odkaz:
https://doaj.org/article/2cac495a33a44514b83079337cb0d132
Publikováno v:
Frontiers in Surgery, Vol 11 (2024)
Hypertensive Intracerebral Hemorrhage (HICH) is one of the most common types of cerebral hemorrhage with a high mortality and disability rate. Currently, preoperative non-contrast computed tomography (NCCT) scanning-guided stereotactic hematoma remov
Externí odkaz:
https://doaj.org/article/c24afa0f157c476db3a64f9a29171bcb