Results 41 to 50 of about 443,004 (222)
Discovering topics in text datasets by visualizing relevant words
When dealing with large collections of documents, it is imperative to quickly get an overview of the texts' contents. In this paper we show how this can be achieved by using a clustering algorithm to identify topics in the dataset and then selecting and visualizing relevant words, which distinguish a group of documents from the rest of the texts, to ...
Horn, Franziska+4 more
openaire +2 more sources
The authors applied joint/mixed models that predict mortality of trifluridine/tipiracil‐treated metastatic colorectal cancer patients based on circulating tumor DNA (ctDNA) trajectories. Patients at high risk of death could be spared aggressive therapy with the prospect of a higher quality of life in their remaining lifetime, whereas patients with a ...
Matthias Unseld+7 more
wiley +1 more source
Breast tumor samples scored for metabolic deregulation (M1 to M3) were given a hypoxia score (HS). The highest HS occurred in patients with strongest metabolic deregulation (M3), supporting tumor aggressiveness. HS correlated with the highest number of metabolic pathways in M1. This suggests hypoxia to be an early event in metabolic deregulation.
Raefa Abou Khouzam+2 more
wiley +1 more source
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran+16 more
wiley +1 more source
Unsupervised Text Topic-Related Gene Extraction for Large Unbalanced Datasets
There is a common notion that traditional unsupervised feature extraction algorithms follow the assumption that the distribution of the different clusters in a dataset is balanced. However, feature selection is guided by the calculation of similarities among features when topic keywords are extracted from a large number of unmarked, unbalanced text ...
Huang Wen-han+5 more
openaire +4 more sources
Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer
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+7 more
wiley +1 more source
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+12 more
wiley +1 more source
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
Text segmentation on multilabel documents: A distant-supervised approach
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
Topic-Conversation Relevance (TCR) Dataset and Benchmarks
To be published in 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and ...
Fan, Yaran+3 more
openaire +2 more sources