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Detecting Associations Based on the Multi-variable Maximum Information Coefficient

Taoyong Gu, Jiansheng Guo, Zhengxin Li, Sheng Mao
2021 IEEE Access  
CONCLUSION In this paper, we propose a multi-variable extension of the maximum information coefficient, and name it as the multi-variable maximum information coefficient (MMIC).  ...  The contributions of this paper can be summarized as follows: • We design a measure based on MIC, and name it as the multi-variable maximum information coefficient (M-MIC).  ...  More detailed codes, data, and results are posted on https: //github.com/GuTaoyong/The-Multi-Variable-Maximum-In formation-Coefficient.  ... 
doi:10.1109/access.2021.3070925 fatcat:kpounnmlffg7dob6z2gedjdheq

OmicsNet: Integration of Multi-Omics Data using Path Analysis in Multilayer Networks [article]

Murodzhon Akhmedov, Alberto Arribas, Roberto Montemanni, Francesco Bertoni, Ivo Kwee
2017 bioRxiv   pre-print
One of the major challenges in systems biology is to develop computational methods for proper integration of multi-omics datasets.  ...  OmicsNet then calculates the highest coefficient paths in multilayer network from each genomic feature to the phenotype by computing an integrated score along the paths.  ...  One can compare pairs (or groups) of h i to detect commonalities or differences in phenotype associated features depending on the phenotype.  ... 
doi:10.1101/238766 fatcat:ewns3si5bzcazg6b43nzz4u2va

Multi-sensor Remote Sensing Image Change Detection: An Evaluation of Similarity Measures

Karthik Ganesan Pillai, Ranga R. Vatsavai
2013 2013 IEEE 13th International Conference on Data Mining Workshops  
Most of the existing approaches are pixel based and rely on direct comparison of radiometric values to detect changes.  ...  Our hypothesis is based on the assumption, that even though images are obtained from different sensors and at different times, the underlying basis in the scene is still the same, since they are different  ...  Maximal Information Coefficient To our best of knowledge, this is the first work in using maximal information coefficient as a measure to detect changes between multi-temporal images.  ... 
doi:10.1109/icdmw.2013.163 dblp:conf/icdm/PillaiV13 fatcat:tep4zadqjjbj7b7we7jrzcdjtm

Identification of patterns of gray matter abnormalities in schizophrenia using source-based morphometry and bagging

Eduardo Castro, Cota Navin Gupta, Manel Martinez-Ramon, Vince D. Calhoun, Mohammad R. Arbabshirani, Jessica Turner
2014 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society  
regions being detected by means of source-based morphometry.  ...  Our method achieves a better classification rate than other algorithms and detects regions with GMC differences between both groups that are consistent with several findings on the literature.  ...  If the contribution of the components to the classification task is evaluated across these data samples, it is possible to detect the most consistently informative ones. II. DATA A.  ... 
doi:10.1109/embc.2014.6943889 pmid:25570257 pmcid:PMC4349445 dblp:conf/embc/CastroGMCAT14 fatcat:2idgpnavdfev3fvvsl3k4gbgha

An invariant descriptor map for 3D objects matching

Abdallah El Chakik, Abdul Rahman El Sayed, Hassan Alabboud, Amer Bakkach
2020 International Journal of Engineering & Technology  
To do so, we compute an invariant shape descriptor map based on 3D surface patches calculated using Zernike coef-ficients.  ...  The matching prob-lem can be formulated as finding the best one-to-one correspondence between featured regions of two shapes.  ...  Consequently, the vertex vi can be described by a single scale descriptor computed based on Zernike coefficients.  ... 
doi:10.14419/ijet.v9i1.29918 fatcat:3tlh22hjjbeffeatgjeagwogny

Non-Laboratory-Based Risk Factors for Automated Heart Disease Detection

H. Mai, T. T. Pham, D. N. Nguyen, E. Dutkiewicz
2018 2018 12th International Symposium on Medical Information and Communication Technology (ISMICT)  
In this work, we aim to develop a non-invasive risk prediction model for automated heart disease detection that involves age, gender, rest blood pressure, maximum heart rate, and rest electrocardiography  ...  Even without laboratory-based data (e.g., serum cholesterol, fasting blood sugar), we observed a prediction accuracy as high as 72%, compared with 76% of other comprehensive models.  ...  Whereas, non-invasive tests provide information about maximum heart rate (MHR), the slope of the peak exercise.  ... 
doi:10.1109/ismict.2018.8573706 dblp:conf/ismict/MaiPND18 fatcat:4pxhskwtf5hgzfhjho7rb6bziu

Parsing radiographs by integrating landmark set detection and multi-object active appearance models

Albert Montillo, Qi Song, Xiaoming Liu, James V. Miller, Sebastien Ourselin, David R. Haynor
2013 Medical Imaging 2013: Image Processing  
Specifically we (1) recover false negative (missing) landmarks through the consensus of inferences from subsets of the detected landmarks, and (2) choose one from multiple false positives for the same  ...  We propose the integration of an automatic detection of a constellation of landmarks via rejection cascade classifiers and a learned geometric constellation subset detector model with a multi-object active  ...  In model learning, one shape model and associated appearance model are trained for the multiple objects based on the manually-labeled radiographs.  ... 
doi:10.1117/12.2007138 pmid:25075265 pmcid:PMC4112100 fatcat:rjv7fwikavc55etkgntxzwesda

Edge Detection using Stationary Wavelet Transform, HMM, and EM algorithm [article]

S.Anand, K.Nagajothi, K.Nithya
2020 arXiv   pre-print
This paper a new edge detection technique using SWT based Hidden Markov Model (WHMM) along with the expectation-maximization (EM) algorithm is proposed.  ...  The SWT coefficients contain a hidden state and they indicate the SWT coefficient fits into an edge model or not.  ...  A new edge detection algorithm WD-HMM using HMM model based on the shift invariant SWT transform is proposed.  ... 
arXiv:2004.11296v1 fatcat:vtt34o3kjjbpvjrjo4jpjwlhle

SuperMIC: Analyzing Large Biological Datasets in Bioinformatics with Maximal Information Coefficient

Chao Wang, Dong Dai, Xi Li, Aili Wang, Xuehai Zhou
2017 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
The maximal information coefficient (MIC) has been proposed to discover relationships and associations between pairs of variables.  ...  Based on the acceleration approach, we extend the traditional two-variable algorithm to multiple variables algorithm.  ...  The framework is based on the analysis of the classic MIC computation for detecting associations between two variables.  ... 
doi:10.1109/tcbb.2016.2550430 pmid:27076457 fatcat:7jtxobwxbba2dhj3wtuz3zsepe

Model selection and assessment for multi-species occupancy models

Kristin M. Broms, Mevin B. Hooten, Ryan M. Fitzpatrick
2016 Ecology  
While multi-species occupancy models (MSOMs) are emerging as a popular method for analyzing biodiversity data, formal checking and validation approaches for this class of models have lagged behind.  ...  Our findings indicated distinct differences among model selection approaches, with cross-validation techniques performing the best in terms of prediction.  ...  The weakly informative priors associated with the MSOM shrunk the standard error to the range we expect for scaled variables on the logit-scale.  ... 
doi:10.1890/15-1471.1 pmid:27859174 fatcat:2o4ndafewfa4dikbrboi3mgp4m

Prostate tumor eccentricity predicts Gleason score better than prostate tumor volume

Rulon Mayer, Charles B. Simone II, Baris Turkbey, Peter Choyke
2021 Quantitative Imaging in Medicine and Surgery  
From multi-parametric MRI, the correlation coefficient R between the Gleason score and the largest blob eccentricity for varying thresholds (0.30 to 0.55) ranged from -0.51 to -0.672 (P<0.01).  ...  Multi-parametric signatures that characterize prostate tumors were inserted into a target detection algorithm (Adaptive Cosine Estimator, ACE).  ...  The identification of the voxel depends on the detection threshold set by the user based on previously examined data, such as optimal correlation with a standard.  ... 
doi:10.21037/qims-21-466 pmid:35111607 pmcid:PMC8739117 fatcat:nmmqiczyxbdirlfrmb7n6yqsl4

NIPMI: A Network Method Based on Interaction Part Mutual Information to Detect Characteristic Genes from Integrated Data on Multi-Cancers

Qian Ding, Junliang Shang, Yan Sun, Guangshuai Liu, Feng Li, XiGUO YUAN, Jin-Xing Liu
2019 IEEE Access  
Herein, the NIPMI method, based on Interaction Part Mutual Information (IPMI) measure for detecting characteristic genes from multi-cancers data, is proposed.  ...  Comprehensive analysis of integrated data on multi-cancers is important for understanding the biological mechanism of these cancers at the system level.  ...  The maximum information coefficient (MIC) is used to detect linear and nonlinear direct correlations between genes.  ... 
doi:10.1109/access.2019.2941520 fatcat:onfqikqygndqraeejtbbkz2tbq

Correlation-based Feature Analysis and Multi-Modality Fusion framework for multimedia semantic retrieval

Hsin-Yu Ha, Yimin Yang, Fausto C. Fleites, Shu-Ching Chen
2013 2013 IEEE International Conference on Multimedia and Expo (ICME)  
based on Maximum Spanning Tree (MaxST) algorithm.  ...  In this paper, we propose a Correlation based Feature Analysis (CFA) and Multi-Modality Fusion (CFA-MMF) framework for multimedia semantic concept retrieval.  ...  In order to take into account the situation where the feature variables follow a nonlinear relationship, we propose another correlation estimation method based on the Spearman's rank correlation coefficients  ... 
doi:10.1109/icme.2013.6607639 dblp:conf/icmcs/HaYFC13 fatcat:yivpfv2eineylcddtrxgrc3vde

Regression-Based Multi-Trait QTL Mapping Using a Structural Equation Model

Xiaojuan Mi, Kent Eskridge, Dong Wang, P. Stephen Baenziger, B. Todd Campbell, Kulvinder S. Gill, Ismail Dweikat, James Bovaird
2010 Statistical Applications in Genetics and Molecular Biology  
Compared with single trait analysis and the multi-trait least-squares analysis, our multi-trait SEM improves statistical power of QTL detection and provides important insight into how QTLs regulate traits  ...  Structural equation modeling (SEM) allows researchers to explicitly characterize the causal structure among the variables and to decompose effects into direct, indirect, and total effects.  ...  Maximum Likelihood (ML): In SEM, the statistical tests are based on the assumption of a multivariate normal distribution for the observed variables.  ... 
doi:10.2202/1544-6115.1552 pmid:21044042 fatcat:i7elkd2ywbc4vd5ahkrrdppore

Multi-sensing based target tracking by using decision-making strategy with spatial and temporal properties

Liu Yang, Liu Xiuju, Jin Huixia, Fu Yuanyuan, Zhang Chi
2019 EURASIP Journal on Wireless Communications and Networking  
The system development is based on sensor spatial and temporal characteristics, and therefore is reliable and stable.  ...  With this strategy, target detection results are obtained and evaluated by probability-based parameters.  ...  Acknowledgements The authors would like to thank all kinds of funds for funding. Funding  ... 
doi:10.1186/s13638-019-1449-6 fatcat:x6nwsz6s2ves5mltv7nacidd6i
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