Whole-slide image analysis identifies a high content of Hodgkin Reed-Sternberg cells and a low content of T lymphocytes in tumor microenvironment as predictors of adverse outcome in patients with classic Hodgkin lymphoma treated with ABVD

Autor: Antonio Santisteban-Espejo, Irene Bernal-Florindo, Jose Perez-Requena, Lidia Atienza-Cuevas, Nieves Maira-Gonzalez, Marcial Garcia-Rojo

Publikováno v: Frontiers in Oncology, Vol 12 (2022)

Classic Hodgkin lymphoma (cHL) constitutes the most frequent lymphoma in young adults. Its histopathology is unique as a scattered tumor population, termed Hodgkin Reed-Sternberg (HRS) cells is diluted in a prominent tumor microenvironment (TME) comp

Externí odkaz: https://doaj.org/article/abf7a99ac17d439cb3453177117653b7

Prognostic Role of the Expression of Latent-Membrane Protein 1 of Epstein–Barr Virus in Classical Hodgkin Lymphoma

Autor: Antonio Santisteban-Espejo, Jose Perez-Requena, Lidia Atienza-Cuevas, Julia Moran-Sanchez, Maria del Carmen Fernandez-Valle, Irene Bernal-Florindo, Raquel Romero-Garcia, Marcial Garcia-Rojo

Publikováno v: Viruses, Vol 13, Iss 12, p 2523 (2021)

The prognostic impact of the presence of Epstein–Barr virus (EBV) in classical Hodgkin lymphoma (cHL) is controversial. Previous studies reported heterogeneous results, rendering difficult the clinical validation of EBV as a prognostic biomarker in

Externí odkaz: https://doaj.org/article/cd55d7cc9e3a45708b457ab5307099b2

Identification of prognostic factors in classic Hodgkin lymphoma by integrating whole slide imaging and next generation sequencing

Autor: Antonio Santisteban-Espejo, Irene Bernal-Florindo, Jose Perez-Requena, Lidia Atienza-Cuevas, Inmaculada Catalina-Fernandez, Maria del Carmen Fernandez-Valle, Raquel Romero-Garcia, Marcial Garcia-Rojo

Publikováno v: Molecular Omics. 18:1015-1028

Digital pathology and genomics are increasingly used to improve our understanding of lymphoid neoplasms. Algorithms for quantifying cell populations in the lymph node and genetics can be integrated to identify new biomarkers with prognostic impact in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4ad4ace1597f75e1f116028851e9e9e
https://doi.org/10.1039/d2mo00195k

Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis

Autor: Miguel Angel Martin-Piedra, Julia Moran-Sanchez, Marcial Garcia-Rojo, Jose Perez-Requena, Antonio Santisteban-Espejo

Publikováno v: Biomolecules
Digibug. Repositorio Institucional de la Universidad de Granada
instname
Volume 11
Issue 6
Biomolecules, Vol 11, Iss 793, p 793 (2021)
Biomolecules 2021, 11(6), 793
RODIN. Repositorio de Objetos de Docencia e Investigación de la Universidad de Cádiz
Digibug: Repositorio Institucional de la Universidad de Granada
Universidad de Granada (UGR)

Genomic analysis and digitalization of medical records have led to a big data scenario within hematopathology. Artificial intelligence and machine learning tools are increasingly used to integrate clinical, histopathological, and genomic data in lymp

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::513a0286a64669c4d25e55d5bc2ebae7
http://hdl.handle.net/10481/68722