Autoencoder-based unsupervised clustering and hashing
Sign Up to like & getrecommendations! Published in 2020 at "Applied Intelligence"
DOI: 10.1007/s10489-020-01797-y
Abstract: Faced with a large amount of data and high-dimensional data information in a database, the existing exact nearest neighbor retrieval methods cannot obtain ideal retrieval results within an acceptable retrieval time. Therefore, researchers have begun… read more here.
Keywords: autoencoder based; based unsupervised; clustering hashing; unsupervised clustering ... See more keywords
Fiber-distance-based unsupervised clustering of MR tractography data
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Neuroscience Methods"
DOI: 10.1016/j.jneumeth.2019.108361
Abstract: BACKGROUND MR tractography from diffusion tensor imaging provides a non-invasive way to explore white matter pathways in the human brain. However, a challenge to extracting reliable anatomical information from these data is the use of… read more here.
Keywords: tractography; fiber distance; unsupervised clustering; dbscan based ... See more keywords
Accurate Molecular-Orbital-Based Machine Learning Energies via Unsupervised Clustering of Chemical Space
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.2c00396
Abstract: We introduce an unsupervised clustering algorithm to improve training efficiency and accuracy in predicting energies using molecular-orbital-based machine learning (MOB-ML). This work determines clusters via the Gaussian mixture model (GMM) in an entirely automatic manner… read more here.
Keywords: gmm; unsupervised clustering; training; orbital based ... See more keywords
Unsupervised clustering to differentiate rheumatoid arthritis patients based on proteomic signatures.
Sign Up to like & getrecommendations! Published in 2023 at "Scandinavian journal of rheumatology"
DOI: 10.1080/03009742.2023.2196781
Abstract: OBJECTIVE Patients with rheumatoid arthritis (RA) have different presentations and prognoses. Cluster analysis based on proteomic signatures creates independent phenogroups of patients with different pathophysiological backgrounds. We aimed to identify distinct pathophysiological clusters of RA… read more here.
Keywords: proteomic signatures; unsupervised clustering; patients based; rheumatoid arthritis ... See more keywords
Multi-omics integration - a comparison of unsupervised clustering methodologies
Sign Up to like & getrecommendations! Published in 2019 at "Briefings in bioinformatics"
DOI: 10.1093/bib/bbx167
Abstract: With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work,… read more here.
Keywords: multi omics; comparison unsupervised; integration; unsupervised clustering ... See more keywords
Safe Semi-Supervised Fuzzy ${C}$ -Means Clustering
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2929307
Abstract: With the rapid increase in the number of collected data samples, semi-supervised clustering (SSC) has become a useful mining tool to find an intrinsic data structure with the help of prior knowledge. The common used… read more here.
Keywords: safe semi; unsupervised clustering; semi supervised; prior knowledge ... See more keywords
Unsupervised Clustering of Seismic Signals Using Deep Convolutional Autoencoders
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2019.2909218
Abstract: In this letter, we use deep neural networks for unsupervised clustering of seismic data. We perform the clustering in a feature space that is simultaneously optimized with the clustering assignment, resulting in learned feature representations… read more here.
Keywords: seismic signals; clustering seismic; deep convolutional; unsupervised clustering ... See more keywords
Unsupervised Clustering-Based Short-Term Solar Forecasting
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Sustainable Energy"
DOI: 10.1109/tste.2018.2881531
Abstract: Solar forecasting accuracy is highly affected by weather conditions, therefore, weather awareness forecasting models are expected to improve the forecasting performance. However, it may not be available or reliable to classify different forecasting tasks by… read more here.
Keywords: method; unsupervised clustering; short term; solar forecasting ... See more keywords
Unsupervised clustering reveals new prostate cancer subtypes
Sign Up to like & getrecommendations! Published in 2017 at "Translational cancer research"
DOI: 10.21037/13778
Abstract: Background: Prostate cancer is the second most common cancer in men. It is urgent to develop a genetic classification for prostate cancer. We aimed to establish the basis of genetic typing. Methods: We used four… read more here.
Keywords: clustering reveals; unsupervised clustering; prostate cancer; cancer ... See more keywords
Assessing Search and Unsupervised Clustering Algorithms in Nested Sampling
Sign Up to like & getrecommendations! Published in 2023 at "Entropy"
DOI: 10.3390/e25020347
Abstract: Nested sampling is an efficient method for calculating Bayesian evidence in data analysis and partition functions of potential energies. It is based on an exploration using a dynamical set of sampling points that evolves to… read more here.
Keywords: unsupervised clustering; nested sampling; clustering algorithms; assessing search ... See more keywords
Using an Unsupervised Clustering Model to Detect the Early Spread of SARS-CoV-2 Worldwide
Sign Up to like & getrecommendations! Published in 2022 at "Genes"
DOI: 10.3390/genes13040648
Abstract: Deciphering the population structure of SARS-CoV-2 is critical to inform public health management and reduce the risk of future dissemination. With the continuous accruing of SARS-CoV-2 genomes worldwide, discovering an effective way to group these… read more here.
Keywords: unsupervised clustering; using unsupervised; sars cov; population ... See more keywords