Zobrazeno 1 - 10
of 1 564
pro vyhledávání: '"COMPUTATIONAL PATHOLOGY"'
Autor:
Alexey Fayzullin, Elena Ivanova, Victor Grinin, Dmitry Ermilov, Svetlana Solovyeva, Maxim Balyasin, Alesia Bakulina, Pavel Nikitin, Yana Valieva, Alina Kalinichenko, Alexander Arutyunyan, Aleksey Lychagin, Peter Timashev
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 24, Iss , Pp 571-582 (2024)
The Banff classification is useful for diagnosing renal transplant rejection. However, it has limitations due to subjectivity and varying concordance in physicians' assessments. Artificial intelligence (AI) can help standardize research, increase obj
Externí odkaz:
https://doaj.org/article/31d73d1268e748ac96599358fd9eb217
Autor:
Andreas Ekholm, Yinxi Wang, Johan Vallon-Christersson, Constance Boissin, Mattias Rantalainen
Publikováno v:
BMC Cancer, Vol 24, Iss 1, Pp 1-13 (2024)
Abstract Background In breast cancer, several gene expression assays have been developed to provide a more personalised treatment. This study focuses on the prediction of two molecular proliferation signatures: an 11-gene proliferation score and the
Externí odkaz:
https://doaj.org/article/4bc232c6cce1401ebf02083c99e6d507
Autor:
Vittorio Bianco, Marika Valentino, Daniele Pirone, Lisa Miccio, Pasquale Memmolo, Valentina Brancato, Luigi Coppola, Giovanni Smaldone, Massimiliano D’Aiuto, Gennaro Mossetti, Marco Salvatore, Pietro Ferraro
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 24, Iss , Pp 225-236 (2024)
Breast cancer is one of the most spread and monitored pathologies in high-income countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and mounted. Conventional inspection of tissue slides under benchtop light microscop
Externí odkaz:
https://doaj.org/article/4fe15282481c46b49e9e0ce03609c987
Autor:
Muhammad Talha Imran, Imran Shafi, Jamil Ahmad, Muhammad Fasih Uddin Butt, Santos Gracia Villar, Eduardo Garcia Villena, Tahir Khurshaid, Imran Ashraf
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-33 (2024)
Abstract Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computational methods to analyze tissue images for more precise disease diagnosis. Traditionally, histopathology relies on manual techniques and exper
Externí odkaz:
https://doaj.org/article/85b98853850b4eb7a10efcce6b12a962
Publikováno v:
Molecular Oncology, Vol 18, Iss 11, Pp 2607-2611 (2024)
The incorporation of novel therapeutic agents such as antibody‐drug conjugates, radio‐conjugates, T‐cell engagers, and chimeric antigen receptor cell therapies represents a paradigm shift in oncology. Cell‐surface target quantification, quant
Externí odkaz:
https://doaj.org/article/9d347ab686e440cd84951119568cca8f
Autor:
Neel Kanwal, Farbod Khoraminia, Umay Kiraz, Andrés Mosquera-Zamudio, Carlos Monteagudo, Emiel A. M. Janssen, Tahlita C. M. Zuiverloon, Chunming Rong, Kjersti Engan
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-25 (2024)
Abstract Background Histopathology is a gold standard for cancer diagnosis. It involves extracting tissue specimens from suspicious areas to prepare a glass slide for a microscopic examination. However, histological tissue processing procedures resul
Externí odkaz:
https://doaj.org/article/d83437ab55034d4695f7d414d324e162
Autor:
Mengke Ma, Wenchao Gu, Yun Liang, Xueping Han, Meng Zhang, Midie Xu, Heli Gao, Wei Tang, Dan Huang
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-14 (2024)
Abstract Background Postoperative liver metastasis significantly impacts the prognosis of pancreatic neuroendocrine tumor (panNET) patients after R0 resection. Combining computational pathology and deep learning radiomics can enhance the detection of
Externí odkaz:
https://doaj.org/article/33843db9e41340af9a33c6eda218aebe
Autor:
Abhinav Sharma, Sandy Kang Lövgren, Kajsa Ledesma Eriksson, Yinxi Wang, Stephanie Robertson, Johan Hartman, Mattias Rantalainen
Publikováno v:
Breast Cancer Research, Vol 26, Iss 1, Pp 1-10 (2024)
Abstract Background Stratipath Breast is a CE-IVD marked artificial intelligence-based solution for prognostic risk stratification of breast cancer patients into high- and low-risk groups, using haematoxylin and eosin (H&E)-stained histopathology who
Externí odkaz:
https://doaj.org/article/efc316e62709488f9a054523aa5c9212
Publikováno v:
Diagnostic Pathology, Vol 19, Iss 1, Pp 1-8 (2024)
Abstract Background Surgical excision with clear histopathological margins is the preferred treatment to prevent progression of lentigo maligna (LM) to invasive melanoma. However, the assessment of resection margins on sun-damaged skin is challenging
Externí odkaz:
https://doaj.org/article/8d471c7b41234f5da5dc92e72c75e172
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-22 (2024)
Abstract Background Cancer pathology shows disease development and associated molecular features. It provides extensive phenotypic information that is cancer-predictive and has potential implications for planning treatment. Based on the exceptional p
Externí odkaz:
https://doaj.org/article/f9c12945bb2e4f9fa3b22bad8f966471