Zobrazeno 1 - 10
of 4 729
pro vyhledávání: '"kernel methods"'
Publikováno v:
BioData Mining, Vol 17, Iss 1, Pp 1-25 (2024)
Abstract Background Advances in high-throughput technologies have originated an ever-increasing availability of omics datasets. The integration of multiple heterogeneous data sources is currently an issue for biology and bioinformatics. Multiple kern
Externí odkaz:
https://doaj.org/article/522d95db6d0149949198edb7d525f99b
Autor:
Emmanuel Ahishakiye, Fredrick Kanobe
Publikováno v:
Discover Artificial Intelligence, Vol 4, Iss 1, Pp 1-16 (2024)
Abstract Background Cervical cancer is the fourth most frequent cancer in women worldwide. Even though cervical cancer deaths have decreased significantly in Western countries, low and middle-income countries account for nearly 90% of cervical cancer
Externí odkaz:
https://doaj.org/article/2be3ce9a56254234af0f4611244b3c9c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Early screening of breast cancer through image recognition technology can significantly increase the survival rate of patients. Therefore, breast cancer pathological image is of great significance for medical diagnosis and clinical research.
Externí odkaz:
https://doaj.org/article/c3899b3643a143458c46d2a7a26391ad
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2024, Iss 1, Pp 1-16 (2024)
Abstract A kernel interpolation method for the acoustic transfer function (ATF) between regions constrained by the physics of sound while being adaptive to the data is proposed. Most ATF interpolation methods aim to model the ATF for fixed source by
Externí odkaz:
https://doaj.org/article/d00a5e9dc9d24efb8e2b893cbae9f12b
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 2, Pp 1126-1144 (2024)
Classification, the task of discerning the class of an unlabeled data point using information from a set of labeled data points, is a well-studied area of machine learning with a variety of approaches. Many of these approaches are closely linked to t
Externí odkaz:
https://doaj.org/article/e6a69eab0af14a01870d912ea0e21858
Autor:
A. Ozier-Lafontaine, C. Fourneaux, G. Durif, P. Arsenteva, C. Vallot, O. Gandrillon, S. Gonin-Giraud, B. Michel, F. Picard
Publikováno v:
Genome Biology, Vol 25, Iss 1, Pp 1-21 (2024)
Abstract Single-cell technologies offer insights into molecular feature distributions, but comparing them poses challenges. We propose a kernel-testing framework for non-linear cell-wise distribution comparison, analyzing gene expression and epigenom
Externí odkaz:
https://doaj.org/article/5e207c347a0b4085b0e247f809decc4d
Autor:
Madeleine Shuhn-Tsuan Yuh, Kendric Ray Ortiz, Kylie Sue Sommer-Kohrt, Meeko Oishi, Neera Jain
Publikováno v:
IEEE Open Journal of Control Systems, Vol 3, Pp 102-117 (2024)
Adaptive automation, automation which is responsive to the human's performance via the alteration of control laws or level of assistance, is an important tool for training humans to attain new skills when operating dynamical systems. When coupled wit
Externí odkaz:
https://doaj.org/article/c574e9e7ef3848e6b38194ddc1a3f430
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-14 (2023)
Abstract Background In this paper, we are interested in interactions between a high-dimensional -omics dataset and clinical covariates. The goal is to evaluate the relationship between a phenotype of interest and a high-dimensional omics pathway, whe
Externí odkaz:
https://doaj.org/article/90824a8c388c4cb39e9a38e1510f6b0f
Autor:
Robin Herkert, Patrick Buchfink, Tizian Wenzel, Bernard Haasdonk, Pavel Toktaliev, Oleg Iliev
Publikováno v:
Mathematics, Vol 12, Iss 13, p 2111 (2024)
We address the challenging application of 3D pore scale reactive flow under varying geometry parameters. The task is to predict time-dependent integral quantities, i.e., breakthrough curves, from the given geometries. As the 3D reactive flow simulati
Externí odkaz:
https://doaj.org/article/890fe491ff9d4484ae442baf1012ca4c
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-21 (2023)
Abstract Background Kernel methods have been proven to be a powerful tool for the integration and analysis of high-throughput technologies generated data. Kernels offer a nonlinear version of any linear algorithm solely based on dot products. The ker
Externí odkaz:
https://doaj.org/article/18fb56440aad4494ac5a8ec171515093