Results 61 to 70 of about 1,745,508 (275)
Deep Short Text Classification with Knowledge Powered Attention
, 2019 Short text classification is one of important tasks in Natural Language Processing (NLP). Unlike paragraphs or documents, short texts are more ambiguous since they have not enough contextual information, which poses a great challenge for classification ...
Chen, Jindong +4 more
core +1 more source
Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Graph Convolutional Networks for Text Classification
, 2018 Text classification is an important and classical problem in natural language processing. There have been a number of studies that applied convolutional neural networks (convolution on regular grid, e.g., sequence) to classification.
Luo, Yuan, Mao, Chengsheng, Yao, Liang
core +1 more source
FEBS Open Bio, EarlyView.RoboMic is an automated confocal microscopy pipeline for high‐throughput functional imaging in living cells. Demonstrated with fluorescence recovery after photobleaching (FRAP), it integrates AI‐driven nuclear segmentation, ROI selection, bleaching, and analysis.
Selçuk Yavuz +6 more
wiley +1 more source
FEBS Open Bio, EarlyView.The inhibition of mitochondrial dihydroorotate dehydrogenase (DHODH) impairs syncytialization and induces cellular senescence via mitochondrial and endoplasmic reticulum stress in human trophoblast stem cells, elevating sFlt1/PlGF levels, a hallmark of placental dysfunction in hypertensive disorders of pregnancy.
Kanoko Yoshida +6 more
wiley +1 more source
Key technology research and model validation of text classification system based on deep learning
Dianxin kexue, 2018 Text classification is very important to text data mining and value exploration.The traditional text classification system has problems of weak feature extraction ability and low classification accuracy.Compared with the traditional text classification ...
Shaomin WANG, Di YANG, Hua REN
doaj +2 more sources
Co-training for Demographic Classification Using Deep Learning from Label Proportions
, 2017 Deep learning algorithms have recently produced state-of-the-art accuracy in many classification tasks, but this success is typically dependent on access to many annotated training examples.
Ardehaly, Ehsan Mohammady, Culotta, Aron
core +1 more source
Screening and epitope characterization of Nidogen‐2‐specific nanobodies
FEBS Open Bio, EarlyView.Camel immunization and phage display were employed to generate high‐affinity VHH nanobodies against Nidogen‐2. After library construction, biopanning, ELISA screening, sequencing, and recombinant expression, selected nanobodies were purified and characterized, leading to the preliminary exploration of a nanobody‐based sandwich ELISA for specific ...
Jianchuan Wen +9 more
wiley +1 more source
Polyseme-Aware Vector Representation for Text Classification
IEEE Access, 2020 Representation models for text classification have recently shown impressive performance. However, these models neglect the importance of polysemous words in text.
Shun Guo, Nianmin Yao
doaj +1 more source
Changes in Immune‐Inflammation Status and Acute Ischemic Stroke Prognosis in Prospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Inflammation is a critical risk factor for poor outcomes in cerebral infarction. Prior studies focused primarily on baseline inflammation status, neglecting dynamic longitudinal changes. We try to investigate the association between immune‐inflammation status alterations and stroke prognosis, and evaluated three systemic biomarkers'
Songfang Chen +11 more
wiley +1 more source