Results 101 to 110 of about 43,712,030 (248)

Web Interface of NER and RE with BERT for Biomedical Text Mining

, 2023
The BioBERT Named Entity Recognition (NER) model is a high-performance model designed to identify both known and unknown entities. It surpasses previous NER models utilized by text-mining tools, such as tmTool and ezTag, in effectively discovering novel ...
Geun-Je Yang, Soo Jun Park, Chae-Bong Sohn, Min-a Lee, Yeon-Ji Park   +4 more
core   +1 more source

Engineered 3D Fibronectin‐Based Environments Modulate the Pathogenic Profile of Arthritic Synovial Fibroblasts

Advanced NanoBiomed Research, EarlyView.
Fibroblast behavior is shaped by the surrounding microenvironment, yet conventional culture systems often fail to capture disease‐relevant phenotypes. Here, platform‐dependent responses of healthy and arthritic synovial fibroblasts are examined across 2D and 3D culture systems. Distinct inflammatory and proliferative signatures emerge, highlighting how
Aneesah Khan, Piaopiao Pan, Yanling Lan, Çağlar Çi̇l, Julia Isakova, Yilin Wang, Theodora Rogkoti, Thanutchaporn Sartyoungkul, James F. C. Windmill, Jonathan William, Manuel Salmeron‐Sanchez, Margaret H. Harnett, Oana Dobre, Miguel A. Pineda   +13 more
wiley   +1 more source

BioVAE: a pre-trained latent variable language model for biomedical text mining. [PDF]

Bioinformatics, 2022
Trieu HL, Miwa M, Ananiadou S.
europepmc   +1 more source

Mining Biomedical Texts for Pediatric Information

Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies, 2021
Tian Yun 0001, Deepti Garg, Natalia Khuri   +2 more
openaire   +2 more sources

Nanomedicine‐driven innovations in postoperative cancer immunotherapy: Remodeling tumor microenvironment and precision delivery strategies

BMEMat, EarlyView.
Nanomedicine‐Driven Strategies for Suppressing Postoperative Tumor Recurrence. This schematic illustrates three pivotal nanomedical strategies that synergistically counteract recurrence by targeting residual disease and the immunosuppressive tumor microenvironment within the surgical cavity.
Lisong Pang, Zhuomin Wang, Zhenhua Jin, Ahmed H. Ghonaim, Hengcheng Zhang, Xinyu You, Jinzhuo Ning, Jiaqing Cao, Yang Liu   +8 more
wiley   +1 more source

BioReader: a text mining tool for performing classification of biomedical literature

BMC Bioinformatics, 2019
Background Scientific data and research results are being published at an unprecedented rate. Many database curators and researchers utilize data and information from the primary literature to populate databases, form hypotheses, or as the basis for ...
Christian Simon, Kristian Davidsen, Christina Hansen, Emily Seymour, Mike Bogetofte Barnkob, Lars Rønn Olsen   +5 more
doaj   +1 more source

A Web Application for Biomedical Text Mining of Scientific Literature Associated with Coronavirus-Related Syndromes: Coronavirus Finder. [PDF]

Diagnostics (Basel), 2022
Armenta-Medina D, Brambila-Tapia AJL, Miranda-Jiménez S, Rodea-Montero ER.   +3 more
europepmc   +1 more source

Genescene: biomedical text and data mining [PDF]

2003 Joint Conference on Digital Libraries, 2003. Proceedings., 2004
Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jennifer Jie Xu 0001, Daniel McDonald, T. Gavin Ng   +10 more
openaire   +2 more sources

Old data, new tricks: Comprehensive computational analysis of 10 years of multi‐center EuroFlow acute myeloid leukemia diagnostic immunophenotypic data

Cytometry Part B: Clinical Cytometry, EarlyView.
Abstract Acute myeloid leukemia (AML) is characterized by high genotypic and immunophenotypic heterogeneity. We collected an extensive dataset containing 5366 flow cytometry files from 885 AML patients, stained with the EuroFlow acute leukemia orientation tube (ALOT) and AML/MDS panel, acquired in a standardized way at eight centers over a period of 10 
Sarah Bonte, Rosan Olsman, Sofie Van Gassen, Sergio Matarraz, Neus Villamor, Stefan Nierkens, Paula Fernandez, Elaine Sobral da Costa, Carmen‐Mariana Aanei, Alberto Orfao, Jacques J. M. van Dongen, Yvan Saeys, Mattias Hofmans, Vincent H. J. van der Velden   +13 more
wiley   +1 more source

Artificial Intelligence in Ophthalmology: From Methodological Advances to Clinical Translation and Future Directions

Eye &ENT Research, EarlyView.
ABSTRACT Artificial intelligence (AI) is reshaping ophthalmology from task‐specific image analysis toward multimodal, longitudinal, and clinically integrated decision support. This narrative review summarizes the methodological evolution of ophthalmic AI, including traditional machine learning, task‐specific deep learning, self‐supervised learning ...
Yuxin Liu, Hanruo Liu
wiley   +1 more source