Results 81 to 90 of about 316,674 (279)
Boosting for named entity recognition [PDF]
proceeding of the 6th conference on Natural language learning - COLING-02, 2002 This paper presents a system that applies boosting to the task of named-entity identification. The CoNLL-2002 shared task, for which the system is designed, is language-independent named-entity recognition. Using a set of features which are easily obtainable for almost any language, the presented system uses boosting to combine a set of weak ...
Dekai Wu +4 more
openaire +1 more source
Advanced Science, EarlyView.This study performs pan‐viromic profiling of 14,529 samples from 5,710 domestic herbivores across five Chinese provinces, establishing the DhCN‐Virome (1,085,360 viral metagenomes). It reveals species/sample‐specific viromic signatures and cross‐species transmission dynamics, aiding unified disease control.
Yue Sun +19 more
wiley +1 more source
Named Entity Recognition Datasets: A Classification Framework
International Journal of Computational Intelligence SystemsNamed entity recognition as a fundamental task plays a crucial role in accomplishing some of the tasks and applications in natural language processing. In the age of Internet information, as far as computer applications are concerned, a huge proportion ...
Ying Zhang, Gang Xiao
doaj +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Advanced Science, EarlyView.Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Mining web data for competency management [PDF]
, 2005 We present CORDER (COmmunity Relation Discovery by named Entity Recognition) an un-supervised machine learning algorithm that exploits named entity recognition and co-occurrence data to associate individuals in an organization with their expertise and ...
Goncalves, A.L. +4 more
core +1 more source
Advanced Science, EarlyView.The FAK‐STAT3‐NNMT axis drives anoikis resistance in circulating tumor cells by reprogramming fatty acid oxidation. Targeting this metabolic vulnerability suppresses metastasis, untangling a key mechanism of breast cancer progression and revealing NNMT as a promising therapeutic target.
Qingchao Tong +13 more
wiley +1 more source
Advanced Science, EarlyView.This review surveys nanoparticle‐based strategies to enhance adoptive cell therapy, particularly CAR‐T cell approaches, in solid tumor treatment. It describes how nanoparticles can improve tumor immunogenicity and T‐cell infiltration while reducing toxicity, and how they enable in vivo CAR‐T cell generation.
Erica Frostegård +19 more
wiley +1 more source
Malay Named Entity Recognition: A Review
Journal of ICT in Education, 2015 The Named Entity Recognition (NER) field had been thriving for more than 15 years. NER could be defined as a process that recognizes named entities, such as the names of persons, organizations, locations, times, and quantities.
Farid Morsidi +4 more
doaj
A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text Mining
IEEE Access, 2019 The amount of biomedical literature is vast and growing quickly, and accurate text mining techniques could help researchers to efficiently extract useful information from the literature.
Donghyeon Kim +8 more
doaj +1 more source
Advanced Science, EarlyView.Multi‐omic profiling of T1 high‐grade bladder cancer identifies a high‐risk subtype (T1HG1) driven by NQO1, which couples anoikis resistance with immune evasion. NQO1 orchestrates macrophage–T cell crosstalk suppression via CXCL9 modulation. Pharmacological NQO1 inhibition with skullcapflavone II enhances cisplatin efficacy, representing a promising ...
Bin Guo +20 more
wiley +1 more source