Results 81 to 90 of about 1,006,138 (295)
Attitudes of cancer patients toward ctDNA‐based liquid biopsy for follow‐up
Molecular Oncology, EarlyView.This mixed‐methods study explored cancer patients' experiences, knowledge, and preferences regarding ctDNA‐based liquid biopsy for follow‐up. Awareness of ctDNA was low and recall of previous liquid biopsy was imperfect, yet acceptance was high.
Siddharth Chhajlani +7 more
wiley +1 more source
Molecular Oncology, EarlyView.Enterotoxigenic Bacteroides fragilis is a gut bacterium linked to bowel cancer. We propose that its toxin acts along two routes: at the cell surface, cutting the adhesion protein E‐cadherin and triggering inflammation; and inside the cell, delivered by bacterial vesicles, switching on NOD1 and cancer stem cell programs.
Kangchan Choi +2 more
wiley +1 more source
Exploring the Privacy-Preserving Properties of Word Embeddings: Algorithmic Validation Study
Journal of Medical Internet Research, 2020 BackgroundWord embeddings are dense numeric vectors used to represent language in neural networks. Until recently, there had been no publicly released embeddings trained on clinical data.
Abdalla, Mohamed +3 more
doaj +1 more source
Word Embeddings with Limited Memory
, 2016 This paper studies the effect of limited precision data representation and computation on word embeddings. We present a systematic evaluation of word embeddings with limited memory and discuss methods that directly train the limited precision ...
Shaoshi Ling +5 more
core +1 more source
Mathematical Aspects of Word Embeddings [PDF]
, 2021 Word embeddings are a popular way of modelling relationships between words. Words are represented as low-dimensional vectors, such that the distances between the vectors reflect relationships between the words: words which are more similar to each other
Carrington, Rachel
core
FEBS Open Bio, EarlyView.Life‐science educators from 14 countries redesigned their own course materials with generative AI in a three‐session, pedagogy‐first FEBS Education and Training Academy workshop built on PICRAT. Among 12 matched respondents, four more reported high confidence in each of five practical domains, and 10 of 13 reported implementing at least one idea ...
Zvonimir Mlinarić, Ali Burak Özkaya
wiley +1 more source
Learning Bilingual Word Embedding Mappings with Similar Words in Related Languages Using GAN
Applied Artificial Intelligence, 2022 Cross-lingual word embeddings display words from different languages in the same vector space. They provide reasoning about semantics, compare the meaning of words across languages and word meaning in multilingual contexts, necessary to bilingual lexicon
Ghafour Alipour +2 more
doaj +1 more source
Applied Sciences, 2021 Obtaining high-quality embeddings of out-of-vocabularies (OOVs) and low-frequency words is a challenge in natural language processing (NLP). To efficiently estimate the embeddings of OOVs and low-frequency words, we propose a new method that uses the ...
Xianwen Liao +5 more
doaj +1 more source
Evaluation of acoustic word embeddings [PDF]
Proceedings of the 1st Workshop on Evaluating Vector-Space
Representations for NLP, 2016 Recently, researchers in speech recognition have started to reconsider using whole words as the basic modeling unit, instead of phonetic units. These systems rely on a function that embeds an arbitrary or fixed dimensional speech segments to a vector in a fixed-dimensional space, named acoustic word embedding.
Sahar Ghannay +3 more
openaire +2 more sources
, 2015 <p>Phrase-level word embeddings for sentiment analysis.</p ...
Liakata, Maria (5296300) +14 more
core +1 more source