Results 31 to 40 of about 4,729 (197)

scTIDE: Deciphering Critical Transitions Through Cell‐Perturbed Manifold Graphs and Optimal Transport Conditional Flow Matching

Advanced Science, EarlyView.
scTIDE identifies single‐cell tipping points by combining manifold‐based graph representations with optimal‐transport conditional flow matching, which preserves intrinsic topology and models distributional dynamics. It supports critical‐transition detection at individual‐cell resolution, prediction of unseen cells, and dimensionality reduction and ...
Jiayuan Zhong, Bowen Niu, Yongbo Yu, Shiyang Nie, Xuerong Gu, Pei Chen, Rui Liu   +6 more
wiley   +1 more source

Manhattan Distance-based K-Medoids Clustering Improvement for Diagnosing Diabetic Disease

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Diabetes is a metabolic disorder characterized by blood glucose levels above normal limits. Diabetes occurs when the body is unable to produce sufficient insulin to regulate blood sugar levels.
Solikhun, Muhammad Rahmansyah Siregar, Lise Pujiastuti, Mochamad Wahyudi   +3 more
doaj   +1 more source

Identifying a Csmd3+ Microglial Subpopulation that Drives Cold‐to‐Hot Transition and Immune‐Cure in Glioblastoma

Advanced Science, EarlyView.
The study establishes an immune‐cure (ICu) mouse model based on a TMEMed G422TN‐GBM system that faithfully recapitulates human TMEMed GBM. scRNA‐seq analysis reveals a Csmd3+ microglial subset with innate immune memory (IIM) potential that potently suppresses GBM growth, drives a TME cold‐to‐hot transition, and induces 100% ICu in long‐term survival ...
Hai‐Feng Jiang, Pan‐Pan Gao, Yu‐Wen Du, Li‐Qin Wu, En‐Zhi Yin, Qi An, Ze‐Hua Ding, Jin‐Wen Shi, Ya Shu, Ruoqiao Chen, Feng Liu, Mingfeng Li, Xiao Qian Chen   +12 more
wiley   +1 more source

Active Distance-Based Clustering Using K-Medoids [PDF]

, 2016
k-medoids algorithm is a partitional, centroid-based clustering algorithm which uses pairwise distances of data points and tries to directly decompose the dataset with $n$ points into a set of $k$ disjoint clusters. However, k-medoids itself requires all distances between data points that are not so easy to get in many applications.
Mehrdad Ghadiri, Amin Aghaee, Mahdieh Soleymani Baghshah   +2 more
openaire   +2 more sources

Cluster Analysis of Circular Economy and Industrial Symbiosis Practices and Their Impact on Sustainability Performance in the Plastics Industry

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines how plastics manufacturing firms can be classified according to their level of implementation of circular economy (CE) and industrial symbiosis (IS) practices and how such adoption influences sustainability performance. Using data from plastics manufacturing firms, we integrate cluster analysis with partial least squares ...
Laura Cristina Ramírez‐Rodríguez, Rafael Mora‐Contreras, Carmen Jaca, Marta Ormazabal   +3 more
wiley   +1 more source

Comparative Study of K-Means Clustering Algorithm and K-Medoids Clustering in Student Data Clustering

JISKA (Jurnal Informatika Sunan Kalijaga), 2022
Universities as educational institutions have very large amounts of academic data which may not be used properly. The data needs to be analyzed to produce information that can map the distribution of students.
Qomariyah, Maria Ulfah Siregar
doaj  

Rockburst intensity prediction in underground buildings based on improved spectral clustering algorithm

Frontiers in Earth Science, 2022
Rockbursts occur in many deep underground excavations and have caused non-negligible casualties or property losses in deep underground building activities over the past hundreds of years.
Zhenzhao Xia, Jingyin Mao, Yao He
doaj   +1 more source

On the Consistency of Metric and Non-Metric K-medoids

, 2020
We establish the consistency of K-medoids in the context of metric spaces. We start by proving that K-medoids is asymptotically equivalent to K-means restricted to the support of the underlying distribution under general conditions, including a wide selection of loss functions. This asymptotic equivalence, in turn, enables us to apply the work of Parna
He Jiang, Ery Arias-Castro
openaire   +3 more sources

Left ventricular function improvement during angiotensin receptor–neprilysin inhibitor treatment in a cohort of HFrEF/HFmrEF patients

ESC Heart Failure, Volume 12, Issue 2, Page 1151-1165, April 2025.
Prediction of LVEF improvement in patients with HFrEF and HFmrEF following treatment with Sacubitril/Valsartan. Workflow of this study investigating the functional capacity improvement in response to Sacubitrail/Valsartsan in a real‐world scenario of heart failure treatment.
Florian Appenzeller, Tobias Harm, Manuel Sigle, Parwez Aidery, Klaus‐Peter Kreisselmeier, Livia Baas, Andreas Goldschmied, Meinrad Paul Gawaz, Karin Anne Lydia Müller   +8 more
wiley   +1 more source

Comparison Of K-Means and K-Medoids Algorithm for Clustering Data UMKM in Pagar Alam City

Jurnal Sisfokom
The aim of this research is clustering MSME data in Pagar Alam City using the K-Means and K-Medoids algorithms. This research is motivated by the lack of further management of MSME data collection, which can hinder the development and improvement of ...
sendy ariska, Desi Puspita, Inda Anggraini   +2 more
doaj   +1 more source