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Scalable Bottom-Up Hierarchical Clustering [article]

Nicholas Monath, Avinava Dubey, Guru Guruganesh, Manzil Zaheer, Amr Ahmed, Andrew McCallum, Gokhan Mergen, Marc Najork, Mert Terzihan, Bryon Tjanaka, Yuan Wang, Yuchen Wu
2020 arXiv   pre-print
Bottom-up algorithms such as the classic hierarchical agglomerative clustering, are highly effective for hierarchical as well as flat clustering.  ...  Our theoretical analysis shows that, under a modest separability assumption, SCC will contain the optimal flat clustering.  ...  Introduction Hierarchical clustering is widely used for tasks such as data analysis and visualization, (Schwartz et al., 2020, inter alia) and entity resolution (Levin et al., Corresponding authors:  ... 
arXiv:2010.11821v2 fatcat:k7ylfbmqpbgbnpexqdt6fivjeu

Editorial

2017 Intelligent Data Analysis  
To solve the problem of appropriate number of clusters automatically, the authors propose the Davies Bouldin Index (DBI) based hierarchical K-means (DHIKM) algorithm on the basis of their previous work  ...  Their results have demonstrated their proposed approach performs better in sensitivity than other approaches compared in the experiment.  ...  Their empirical analysis and the comparison with the most known methods proves the significance of this approach.  ... 
doi:10.3233/ida-170888 fatcat:zfn4ifgyavcxjptt7w4hx6rgte

Pathway Analysis of Genomic Pathology Tests for Prognostic Cancer Subtyping

Olga Lyudovyk, Yufeng Shen, Nicholas P Tatonetti, Susan J Hsiao, Mahesh M Mansukhani, Chunhua Weng
2019 Journal of Biomedical Informatics  
We demonstrate that this approach identifies subtypes of prognostic value and biological pathways linked to survival, with implications for precision treatment selection and a better understanding of the  ...  We also share lessons learned regarding the opportunities and challenges of secondary use of observational genomic data to conduct such research.  ...  Acknowledgments Authors would like to thank David Fasel and Ben May for assistance in the extraction of EHR and Tumor Registry data, Dr.  ... 
doi:10.1016/j.jbi.2019.103286 pmid:31499184 pmcid:PMC7136846 fatcat:o23rludyo5ef5j43v3iry5hasy

Overview of PAN'17 [chapter]

Martin Potthast, Francisco Rangel, Michael Tschuggnall, Efstathios Stamatatos, Paolo Rosso, Benno Stein
2017 Lecture Notes in Computer Science  
Abstract The PAN 2017 shared tasks on digital text forensics were held in conjunction with the annual CLEF conference.  ...  For each task, we give a brief summary of the evaluation data, performance measures, and results obtained.  ...  Acknowledgements Our special thanks go to all of PAN's participants, to Symanto Group 2 for sponsoring PAN and to MeaningCloud 3 for sponsoring the author profiling shared task award.  ... 
doi:10.1007/978-3-319-65813-1_25 fatcat:mwcxd74zmvf6jdf243ur2t7a4y

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

Sugeerth Murugesan, Kristofer Bouchard, Edward Chang, Max Dougherty, Bernd Hamann, Gunther H. Weber
2017 BMC Bioinformatics  
The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters  ...  Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its  ...  Acknowledgments The authors are thankful to the editors and reviewers who provided us with valuable comments to improve the manuscript.  ... 
doi:10.1186/s12859-017-1633-9 pmid:28617218 pmcid:PMC5471943 fatcat:5dvcauho65hvnb7n4e2al6ulva

Automatic multi-resolution shape modeling of multi-organ structures

Juan J. Cerrolaza, Mauricio Reyes, Ronald M. Summers, Miguel Ángel González-Ballester, Marius George Linguraru
2015 Medical Image Analysis  
The resulting algorithm, named GEMA, provides a better overall performance than the two classical approaches tested, ASM, and hierarchical ASM, when applied to the segmentation of 3D brain MRI.  ...  Importantly, unlike previous approaches, the configuration of the algorithm is automated thanks to a new agglomerative landmark clustering method proposed here, which equally allows us to identify smaller  ...  We also like to thank the Intramural Research Program of the National Institute of Health, Clinical Center.  ... 
doi:10.1016/j.media.2015.04.003 pmid:25977156 pmcid:PMC5526337 fatcat:nlpmvgrlw5gypfrkx4tfkgzubq

New Tools in Orthology Analysis: A Brief Review of Promising Perspectives

Bruno T. L. Nichio, Jeroniza Nunes Marchaukoski, Roberto Tadeu Raittz
2017 Frontiers in Genetics  
We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool  ...  high processing time to complete the analysis.  ...  a lot of time to perform its task.  ... 
doi:10.3389/fgene.2017.00165 pmid:29163633 pmcid:PMC5674930 fatcat:kl53wnq3unaxpoytoutf66olry

Multi-Scale Analysis of Very High Resolution Satellite Images Using Unsupervised Techniques

Jérémie Sublime, Andrés Troya-Galvis, Anne Puissant
2017 Remote Sensing  
In particular, one of the main contributions of this article comes in the form of a multi-scale analysis clustering algorithm that we use during the processing of the image segments.  ...  Our proposed methods are tested on a very high resolution image (Pléiades) of the urban area around the French city of Strasbourg and show relevant results at each step of the process.  ...  The authors would like to thank the Pléiades Users Thematic Commissioning, Program ORFEO (Optical and Radar Federated Earth Observation) Accompaniment Program (CNES), for Pléiades images availability.  ... 
doi:10.3390/rs9050495 fatcat:2tsmfldyjrdtbj6vob6keaiegy

Relating anomaly correlation to lead time: Clustering analysis of CFSv2 forecasts of summer precipitation in China

Tongtiegang Zhao, Pan Liu, Yongyong Zhang, Chengqing Ruan
2017 Journal of Geophysical Research - Atmospheres  
The robustness of the patterns has been tested using both hierarchical clustering and k-means clustering and examined with the Silhouette score.  ...  The vectors of anomaly correlation across different GCM grid cells are clustered to reveal how GCM forecasts perform as time progresses.  ...  The first author is in particular grateful to the State Key Laboratory of Water Resources and Hydro-power Engineering at Wuhan University for the support (2016SWK01).  ... 
doi:10.1002/2017jd027018 fatcat:2frugvrasbaojo4frscudctpqe

Deep Learning Based Analysis of Histopathological Images of Breast Cancer

Juanying Xie, Ran Liu, Joseph Luttrell, Chaoyang Zhang
2019 Frontiers in Genetics  
We also constructed a new autoencoder network to transform the features extracted by Inception_ResNet_V2 to a low dimensional space to do clustering analysis of the images.  ...  Therefore, we used Inception_ResNet_V2 to extract features from breast cancer histopathological images to perform unsupervised analysis of the images.  ...  ACKNOWLEDGMENTS The authors would like to thank Professor Spanhol et al. who  ... 
doi:10.3389/fgene.2019.00080 pmid:30838023 pmcid:PMC6390493 fatcat:rnoqwpq6branhiv3p6z75caphq

ParticleMDI: particle Monte Carlo methods for the cluster analysis of multiple datasets with applications to cancer subtype identification

Nathan Cunningham, Jim E. Griffin, David L. Wild
2020 Advances in Data Analysis and Classification  
We present a novel nonparametric Bayesian approach for performing cluster analysis in a context where observational units have data arising from multiple sources.  ...  We develop several approaches to improving the computational performance of our algorithm.  ...  Many approaches to integrative cluster analysis exist: performing cluster analysis at the level of underlying latent variables (see, e.g., Shen et al. 2009; Gabasova et al. 2017; McParland et al. 2014  ... 
doi:10.1007/s11634-020-00401-y fatcat:z72gmj62qra7dck2t6dmp3rzbu

Medal: a patient similarity metric using medication prescribing patterns [article]

Arturo Lopez Pineda, Armin Pourshafeie, Alexander Ioannidis, Collin McCloskey Leibold, Avis Chan, Jennifer Frankovich, Carlos D. Bustamante, Genevieve L. Wojcik
2019 medRxiv   pre-print
After calculating a distance metric with Medal, we compute a hierarchical clustering and explore the most appropriate number of clusters.  ...  We identified four clusters in PANS with distinct medication usage histories, driven primarily by penicillin.  ...  "patient stopped NSAIDs March 2017" would be coded as Patient outcomes In the PANS cohort, like in many other psychiatric syndromes, evaluating outcomes is a complex task which requires the use of scales  ... 
doi:10.1101/19004440 fatcat:3o7go6bmivh6dmgxhy7smolngu

A review of infant cry analysis and classification

Chunyan Ji, Thosini Bamunu Mudiyanselage, Yutong Gao, Yi Pan
2021 EURASIP Journal on Audio, Speech, and Music Processing  
AbstractThis paper reviews recent research works in infant cry signal analysis and classification tasks.  ...  This survey systematically studies the previous research in all relevant areas of infant cry and provides an insight on the current cutting-edge works in infant cry signal analysis and classification.  ...  Acknowledgements The authors would like to thank the editors and reviewers for their valuable suggestions.  ... 
doi:10.1186/s13636-021-00197-5 fatcat:i36trhygcne4nfyx3wc7g4h4ki

Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis

Majd Zreik, Nikolas Lessmann, Robbert W. van Hamersvelt, Jelmer M. Wolterink, Michiel Voskuil, Max A. Viergever, Tim Leiner, Ivana Išgum
2018 Medical Image Analysis  
The results demonstrate that automatic analysis of the LV myocardium in a single CCTA scan acquired at rest, without assessment of the anatomy of the coronary arteries, can be used to identify patients  ...  To identify patients with a functionally significant coronary artery stenosis, analysis is performed in several stages.  ...  analysis of medical images in a range of seg- mentation and detection tasks (Litjens et al., 2017; Shen et al., 2017; Zhou et al., 2017), is employed.  ... 
doi:10.1016/j.media.2017.11.008 pmid:29197253 fatcat:k4uv4aot5ffizoq7cfww4mjobu

Discovering prescription patterns in pediatric acute-onset neuropsychiatric syndrome patients

Arturo Lopez Pineda, Armin Pourshafeie, Alexander Ioannidis, Collin McCloskey Leibold, Avis L. Chan, Carlos D. Bustamante, Jennifer Frankovich, Genevieve L. Wojcik
2021 Journal of Biomedical Informatics  
The psychometric scores as outcomes in each cluster generally improved within the first two years. and conclusion Our algorithm shows potential to improve our knowledge of treatment patterns in the PANS  ...  We developed a modified dynamic programming approach to perform global alignment of those medication histories.  ...  The path starts from the bottom-right cell and ends at the top-left cell of the matrix. Fig. 4 . 4 Analysis of optimal number of clusters.  ... 
doi:10.1016/j.jbi.2020.103664 pmid:33359113 fatcat:rvf4tl7i3fdjtb5pj3rn5xge7i
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