Results 71 to 80 of about 6,752,678 (299)

Community-Aware Evolution Similarity for Link Prediction in Dynamic Social Networks

Mathematics
The link prediction problem is a time-evolving model in network science that has simultaneously abetted myriad applications and experienced extensive methodological improvement. Inferring the possibility of emerging links in dynamic social networks, also
Nazim Choudhury
doaj   +1 more source

A Method for Improving the Accuracy of Link Prediction Algorithms

Complexity, 2021
Link prediction is a key tool for studying the structure and evolution mechanism of complex networks. Recommending new friend relationships through accurate link prediction is one of the important factors in the evolution, development, and popularization
Jie Li, Xiyang Peng, Jian Wang, Na Zhao
doaj   +1 more source

A PRSZT Registry Analysis of Prognostic Factors Influencing Survival and Relapse Rates After Second Allogeneic Hematopoietic Stem Cell Transplantation in Pediatric Acute Lymphoblastic Leukemia

Pediatric Blood &Cancer, EarlyView.
ABSTRACT A second allogeneic (allo‐)hematopoietic stem cell transplantation (HSCT2) is a potential curative option for pediatric patients with acute lymphoblastic leukemia (ALL) following relapse after first allogeneic transplantation (HSCT1), but its efficacy is limited by high relapse rates and transplant‐related toxicity in highly pretreated ...
Ava Momm, Imme Haubitz, Rita Beier, Martin Zimmermann, Andrej Lissat, Peter Bader, Matthias Eyrich, Jan‐Henning Klusmann, Matthias Wölfl, Paul‐Gerhardt Schlegel, Verena Wiegering   +10 more
wiley   +1 more source

Improving embedding-based link prediction performance using clustering

Journal of King Saud University: Computer and Information Sciences
Incomplete knowledge graphs are common problem that can impair task accuracy. As knowledge graphs grow extensively, the probability of incompleteness increases.
Fitri Susanti, Nur Ulfa Maulidevi, Kridanto Surendro   +2 more
doaj   +1 more source

Graph Neural Networks for Link Prediction

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023
Graph Neural Networks (GNNs) belong to a class of deep learning methods that are specialized for extracting critical information and making accurate predictions on graph representations.
Alina Lazar
doaj   +1 more source

Learning from Counterfactual Links for Link Prediction

, 2021
Accepted by ICML ...
Zhao, Tong, Liu, Gang, Wang, Daheng, Yu, Wenhao, Jiang, Meng   +4 more
openaire   +2 more sources

Upacicalcet: A Novel Intravenous Calcimimetic Agent for Patients Undergoing Hemodialysis With Secondary Hyperparathyroidism

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Secondary hyperparathyroidism (SHPT) is a common complication in patients receiving maintenance dialysis, driven by calcium and phosphate metabolism disturbances. Calcimimetics are central to the management of SHPT by enhancing calcium‐sensing receptor sensitivity and reducing parathyroid hormone secretion.
Fumihiko Koiwa, Daisuke Honda, Seigo Akari, Tadao Akizawa   +3 more
wiley   +1 more source

Weighted enclosing subgraph-based link prediction for complex network

EURASIP Journal on Wireless Communications and Networking, 2022
Link prediction is a fundamental research issue in complex network, which can reveal the potential relationships between users. Most of link prediction algorithms are heuristic and based on topology structure.
Weiwei Yuan, Yun Han, Donghai Guan, Guangjie Han, Yuan Tian, Abdullah Al-Dhelaan, Mohammed Al-Dhelaan   +6 more
doaj   +1 more source

Mapping the evolution of mitochondrial complex I through structural variation

FEBS Letters, EarlyView.
Respiratory complex I (CI) is crucial for bioenergetic metabolism in many prokaryotes and eukaryotes. It is composed of a conserved set of core subunits and additional accessory subunits that vary depending on the organism. Here, we categorize CI subunits from available structures to map the evolution of CI across eukaryotes. Respiratory complex I (CI)
Dong‐Woo Shin, Tingting Chen, James A. Letts   +2 more
wiley   +1 more source

Study on AdaBoost-based link quality prediction mechanism

Tongxin xuebao, 2017
The link quality was vulnerable to the complexity environment in wireless sensor network.Obtaining link quality information in advance could reduce energy consumption of nodes.After analyzing the existing link quality prediction methods,AdaBoost-based ...
Jian SHU, Man-lan LIU, Wei ZHENG
doaj   +2 more sources