Zobrazeno 1 - 10
of 286
pro vyhledávání: '"pathomics"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Pancreatic cancer exhibits a high degree of malignancy with a poor prognosis, lacking effective prognostic targets. Utilizing histopathological methodologies, this study endeavors to predict the expression of pathological features in pancrea
Externí odkaz:
https://doaj.org/article/0a1a3ac2b38d4846b39078a0e96609cd
Publikováno v:
Big Data Mining and Analytics, Vol 7, Iss 3, Pp 590-602 (2024)
Kirsten rat sarcoma viral oncogene homolog (namely KRAS) is a key biomarker for prognostic analysis and targeted therapy of colorectal cancer. Recently, the advancement of machine learning, especially deep learning, has greatly promoted the developme
Externí odkaz:
https://doaj.org/article/e5318c9013be456dab7a3a654e626975
Publikováno v:
Heliyon, Vol 10, Iss 20, Pp e38562- (2024)
Background: Enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) is overexpressed in hepatocellular carcinoma, promoting tumorigenesis and correlating with poor prognosis. Traditional histopathological examinations are insufficient to acc
Externí odkaz:
https://doaj.org/article/7bb474165a474c87a3cdf3ae978038d4
Autor:
Yixian Wang, Xin Li, Qingwei Gang, Yinde Huang, Mingyu Liu, Han Zhang, Shikai Shen, Yao Qi, Jian Zhang
Publikováno v:
BMC Cancer, Vol 24, Iss 1, Pp 1-15 (2024)
Abstract Background Papillary thyroid carcinoma (PTC) is globally prevalent and associated with an increased risk of lymph node metastasis (LNM). The role of cancer-associated fibroblasts (CAFs) in PTC remains unclear. Methods We collected postoperat
Externí odkaz:
https://doaj.org/article/c5cf5bae779748c4975dcb78ddf2983b
Autor:
Xiang Li, Casey C. Heirman, Ashlyn G. Rickard, Gina Sotolongo, Rico Castillo, Temitayo Adanlawo, Jeffery I. Everitt, Jeffery B. Hodgin, Tammara L. Watts, Andrew Janowczyk, Yvonne M. Mowery, Laura Barisoni, Kyle J. Lafata
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
IntroductionImmune dysregulation plays a major role in cancer progression. The quantification of lymphocytic spatial inflammation may enable spatial system biology, improve understanding of therapeutic resistance, and contribute to prognostic imaging
Externí odkaz:
https://doaj.org/article/108dd592c3f5483aba2e29aba84f2c13
Autor:
Deepak Chandramohan, Hari Naga Garapati, Udit Nangia, Prathap K. Simhadri, Boney Lapsiwala, Nihar K. Jena, Prabhat Singh
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
IntroductionThe prevalence of Renal cell carcinoma (RCC) is increasing among adults. Histopathologic samples obtained after surgical resection or from biopsies of a renal mass require subtype classification for diagnosis, prognosis, and to determine
Externí odkaz:
https://doaj.org/article/2ce440b272af4554a2c51aac927b7fed
Publikováno v:
Heliyon, Vol 10, Iss 17, Pp e37100- (2024)
Objective: This study aimed to predict the level of stemness index (mRNAsi) and survival prognosis of lung adenocarcinoma (LUAD) using pathomics model. Methods: From The Cancer Genome Atlas (TCGA) database, 327 LUAD patients were randomly assigned to
Externí odkaz:
https://doaj.org/article/0863fac8b99f41cd890b71f8ed432e61
Publikováno v:
BMC Cancer, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Objective This study aimed to develop and validate an artificial intelligence radiopathological model using preoperative CT scans and postoperative hematoxylin and eosin (HE) stained slides to predict the pathological staging of gastric canc
Externí odkaz:
https://doaj.org/article/a1d58a891398497fb252e7dae5bf52c9
Autor:
David L. Hölscher, Michael Goedertier, Barbara M. Klinkhammer, Patrick Droste, Ivan G. Costa, Peter Boor, Roman D. Bülow
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-11 (2024)
Abstract Background Pathomics facilitates automated, reproducible and precise histopathology analysis and morphological phenotyping. Similar to molecular omics, pathomics datasets are high-dimensional, but also face large outlier variability and inhe
Externí odkaz:
https://doaj.org/article/b0d0aa69d8504016b2e20a8120906e4d
Publikováno v:
Translational Oncology, Vol 51, Iss , Pp 102174- (2025)
Objective: This study aims to develop and validate a radiopathomics model that integrates radiomic and pathomic features to predict overall survival (OS) in hepatocellular carcinoma (HCC) patients. Materials and methods: This study involved 126 HCC p
Externí odkaz:
https://doaj.org/article/77f15db48b7840b2ace1ebd8ea894306