Results 71 to 80 of about 745,152 (307)
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Osteosarcoma (OS) and Ewing sarcoma (EWS) are the most common primary bone cancers in children, but acute thrombosis is poorly characterized in this population. Our study evaluated the rates of venous thromboembolism (VTE) and associated risk factors in pediatric patients with bone sarcomas treated over a 10‐year period encompassing
Sarah Kappa +8 more
wiley +1 more source
Sentence level relation extraction via relation embedding
, 2021 Relation extraction is a task of information extraction that extracts semantic relations from text, which usually occur between two named entities. It is a crucial step for converting unstructured text into structured data that forms a knowledge base, so
Huang, Haojie
core +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Claudin‐6 has emerged as a promising immunotherapeutic target, yet protein‐level data in atypical teratoid/rhabdoid tumors (AT/RTs) have been inconsistent. We analyzed 36 well‐characterized AT/RT samples and found membranous claudin‐6 protein expression in 58% of cases, with striking enrichment in the molecular subgroup AT/RT‐TYR (100%) and ...
Victoria E. Fincke +4 more
wiley +1 more source
Applied Sciences, 2023 Relation extraction tasks aim to predict the type of relationship between two entities from a given text. However, many existing methods fail to fully utilize the semantic information and the probability distribution of the output of pre-trained language
Ping Feng +4 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Wilms tumor (WT) treatment imposes a significant time burden on patients and their families. Time toxicity is a patient‐centered metric that quantifies the burden of healthcare interaction. We sought to define time toxicity in the first year after diagnosis of WT and hypothesized that it would increase as tumor stage and treatment ...
Caleb Q. Ashbrook +6 more
wiley +1 more source
Adversarial Training for Relation Extraction [PDF]
Proceedings of the 2017 Conference on Empirical Methods in Natural
Language Processing, 2017 Adversarial training is a mean of regularizing classification algorithms by generating adversarial noise to the training data. We apply adversarial training in relation extraction within the multi-instance multi-label learning framework. We evaluate various neural network architectures on two different datasets.
Yi Wu 0013 +2 more
openaire +1 more source
Towards relation extraction from speech [PDF]
, 2022 Relation extraction has focused on extracting semantic relationships between entities from the unstructured written textual data. However, with the vast and rapidly increasing amounts of spoken data, relation extraction from speech is an important but ...
Liu, Zhaoran +6 more
core
Applied Sciences, 2022 The main purpose of the joint entity and relation extraction is to extract entities from unstructured texts and extract the relation between labeled entities at the same time. At present, most existing joint entity and relation extraction networks ignore
Huiyan Wu, Jun Huang
doaj +1 more source
The Role of Hematopoietic Cell Transplantation in Ataxia‐Telangiectasia
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Ataxia‐telangiectasia (A‐T) is a DNA repair disorder characterized by neurodegeneration, immunodeficiency, and cancer predisposition. Hematopoietic cell transplantation (HCT) is an established therapy in related disorders such as Fanconi anemia (FA) and Nijmegen breakage syndrome (NBS), but its role in A‐T is unclear.
Laila Alkhouli +3 more
wiley +1 more source
CrowdTruth Corpus for Open Domain Relation Extraction from Sentences
, 2018 <p>This repository contains a ground truth corpus for open domain relation extraction from sentences, acquired with crowdsourcing and processed with <strong><a href="http://crowdtruth.org/">CrowdTruth</a></strong> metrics ...
Lora Aroyo +5 more
core +1 more source