Results 81 to 90 of about 1,881,625 (304)

Bibliometric Analysis to Scan and Scrape New Datasets: It’s all about that BASS

International Journal of Population Data Science, 2017
Objectives The main objective of this poster is to present a pilot project in determining emerging population health themes and identifying key research-enabling datasets ahead of time.
Karen Tingay, Brian Perkins, Athanasios Anastasiou   +2 more
doaj   +1 more source

Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer

Molecular Oncology, EarlyView.
This study employed targeted metabolomic profiling to identify 302 distinct metabolites present in platelet‐rich plasma (PRP), revealing aberrant metabolic profiles amongst individuals diagnosed with colorectal cancer (CRC). Compared to carcinoembryonic antigen (CEA) and cancer antigen 19‐9 (CA199), our metabolite panel showed improved sensitivity ...
Zuojian Hu, Fenglin Shen, Yang Liu, Ziqing Zhong, Yongling Chen, Zhiyuan Xia, Cuiju Mo, Hongxiu Yu   +7 more
wiley   +1 more source

Inhibition of acyl‐CoA synthetase long‐chain isozymes decreases multiple myeloma cell proliferation and causes mitochondrial dysfunction

Molecular Oncology, EarlyView.
Triacsin C inhibition of the acyl‐CoA synthetase long chain (ACSL) family decreases multiple myeloma cell survival, proliferation, mitochondrial respiration, and membrane potential. Made with Biorender.com. Multiple myeloma (MM) is an incurable cancer of plasma cells with a 5‐year survival rate of 59%.
Connor S. Murphy, Heather Fairfield, Victoria E. DeMambro, Samaa Fadel, Carlos A. Gartner, Michelle Karam, Christian Potts, Princess Rodriguez, Ya‐Wei Qiang, Habib Hamidi, Xiangnan Guan, Calvin P. H. Vary, Michaela R. Reagan   +12 more
wiley   +1 more source

Integration of Neural Embeddings and Probabilistic Models in Topic Modeling

Applied Artificial Intelligence
Topic modeling, a way to find topics in large volumes of text, has grown with the help of deep learning. This paper presents two novel approaches to topic modeling by integrating embeddings derived from Bert-Topic with the multi-grain clustering topic ...
Pantea Koochemeshkian, Nizar Bouguila
doaj   +1 more source

Language Model-Driven Topic Clustering and Summarization for News Articles

IEEE Access, 2019
Topic models have been widely utilized in Topic Detection and Tracking tasks, which aim to detect, track, and describe topics from a stream of broadcast news reports.
Peng Yang, Wenhan Li, Guangzhen Zhao
doaj   +1 more source

Integration of single‐cell and bulk RNA‐sequencing data reveals the prognostic potential of epithelial gene markers for prostate cancer

Molecular Oncology, EarlyView.
Prostate cancer is a leading malignancy with significant clinical heterogeneity in men. An 11‐gene signature derived from dysregulated epithelial cell markers effectively predicted biochemical recurrence‐free survival in patients who underwent radical surgery or radiotherapy.
Zhuofan Mou, Lorna W. Harries
wiley   +1 more source

Contextual topic discovery using unsupervised keyphrase extraction and hierarchical semantic graph model

Journal of Big Data, 2023
Recent technological advancements have led to a significant increase in digital documents. A document’s key information is generally represented by the keyphrases that provide the abstract description contained therein.
Hung Du, Srikanth Thudumu, Antonio Giardina, Rajesh Vasa, Kon Mouzakis, Li Jiang, John Chisholm, Sanat Bista   +7 more
doaj   +1 more source

Text segmentation on multilabel documents: A distant-supervised approach

, 2019
Segmenting text into semantically coherent segments is an important task with applications in information retrieval and text summarization. Developing accurate topical segmentation requires the availability of training data with ground truth information ...
Karypis, George, Manchanda, Saurav
core   +1 more source

Statistically validated network for analysing textual data

Applied Network Science
This paper presents a novel methodology, called Word Co-occurrence SVN topic model (WCSVNtm), for document clustering and topic modeling in textual datasets.
Andrea Simonetti, Alessandro Albano, Michele Tumminello, T. Di Matteo   +3 more
doaj   +1 more source

Multi-scale Hybridized Topic Modeling: A Pipeline for Analyzing Unstructured Text Datasets via Topic Modeling

, 2022
We propose a multi-scale hybridized topic modeling method to find hidden topics from transcribed interviews more accurately and efficiently than traditional topic modeling methods. Our multi-scale hybridized topic modeling method (MSHTM) approaches data at different scales and performs topic modeling in a hierarchical way utilizing first a classical ...
Cheng, Keyi, Inzer, Stefan, Leung, Adrian, Shen, Xiaoxian, Perlmutter, Michael, Lindstrom, Michael, Chew, Joyce, Presner, Todd, Needell, Deanna   +8 more
openaire   +2 more sources