Results 51 to 60 of about 574,210 (309)

A Novel Representation of Neural Networks

CoRR, 2016
Deep Neural Networks (DNNs) have become very popular for prediction in many areas. Their strength is in representation with a high number of parameters that are commonly learned via gradient descent or similar optimization methods. However, the representation is non-standardized, and the gradient calculation methods are often performed using component ...
Anthony L. Caterini, Dong Eui Chang
openaire   +2 more sources

Health‐Related Quality of Life and Symptom Severity Among Patients With PIK3CA‐Related Overgrowth Spectrum: A Mixed‐Methods Study to Understand Real‐World Experience With Alpelisib Treatment

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background PIK3CA‐related overgrowth spectrum (PROS) includes several rare overgrowth disorders resulting from somatic gain‐of‐function mutations in PIK3CA. Despite treatment advances, including the recent approval of alpelisib for PROS in the United States, literature detailing the patient experience with PROS is limited.
Vamsi Bollu, Kaitlin LaGasse, Cory D. Saucier, Kimberly Raymond, Miranda Lauher‐Charest, Lauren Crowder, Beilei Cai, Mary Lisha Paul, Denise Adams   +8 more
wiley   +1 more source

Heterogeneity in the Global Practice of Central Nervous System Staging in Pediatric Acute Lymphoblastic Leukemia

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Central nervous system (CNS) involvement in childhood acute lymphoblastic leukemia (ALL) is assessed by cell counting and cytomorphology from cerebrospinal fluid (CSF) and is used for treatment stratification worldwide. The ratio of “CNS2” patients in clinical trials ranges from 3% to 40%, with unclear prognostic significance ...
Laura Almási, Bernadett Borbála Huszti, Gábor Barna, Marko Kavcic, Janez Jazbec, Lennart Lenk, Vera Münch, Sophia Polychronopoulou, Ágnes Márk, Maria Thastrup, Lüder H. Meyer, Kjeld Schmiegelow, Cornelia Eckert, Christina Halsey, Dániel J. Erdélyi   +14 more
wiley   +1 more source

Ten years of knowledge representation for health care (2009–2018): Topics, trends, and challenges [PDF]

, 2019
Background: In the last ten years, the international workshop on knowledge representation for health care (KR4HC) has hosted outstanding contributions of the artificial intelligence in medicine community pertaining to the formalization and representation
Peleg, Mor, ten Teije, Annette, Riaño, David, ten Teije, Annette; id_orcid   +3 more
core   +1 more source

Representation Alignment in Neural Networks

Trans. Mach. Learn. Res., 2021
It is now a standard for neural network representations to be trained on large, publicly available datasets, and used for new problems. The reasons for why neural network representations have been so successful for transfer, however, are still not fully understood.
Ehsan Imani, Wei Hu, Martha White
openaire   +3 more sources

Increased Risk of Sarcomas in Children With Congenital Anomalies: Findings From the Genetic Overlap Between Anomalies and Cancer in Kids (GOBACK) Registry Linkage Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Pediatric sarcomas are a heterogeneous group of tumors that contribute disproportionately to cancer mortality in children. Although congenital anomalies are among the strongest known risk factors for childhood cancer, the risk of specific sarcoma subtypes among affected individuals has not yet been thoroughly evaluated. Procedure We
Russ Wolters, Ji Yun Tark, Tiffany M. Chambers, Tania A. Desrosiers, Michael E. Scheurer, Charles Shumate, Wendy N. Nembhard, Mahsa M. Yazdy, Eirini Nestoridi, Amanda E. Janitz, Jean Paul Tanner, Russell S. Kirby, Jason L. Salemi, Yao Yu, Chad D. Huff, Sharon E. Plon, Philip J. Lupo, Jeremy M. Schraw   +17 more
wiley   +1 more source

A Network Representation Learning Model Based on Multiple Remodeling of Node Attributes

Mathematics, 2023
Current network representation learning models mainly use matrix factorization-based and neural network-based approaches, and most models still focus only on local neighbor features of nodes.
Wei Zhang, Baoyang Cui, Zhonglin Ye, Zhen Liu   +3 more
doaj   +1 more source

A Bibliometric Analysis of Publications in Uremic Toxins From 1991 to 2024

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Uremic toxins are a growing area of research in nephrology, with significant implications in the progression and treatment of chronic kidney disease (CKD) and the management of end‐stage kidney disease (ESKD). This bibliometric analysis aims to evaluate the global research trends, key contributors, and the impact of publications in ...
Yuh‐Shan Ho, Karim M. Soliman, Wisit Cheungpasitporn, Wannasit Wathanavasin, Ahmed Daoud, Ahmed I. Kamal, Balázs Szamosfalvi, Tibor Fülöp   +7 more
wiley   +1 more source

An Information-Explainable Random Walk Based Unsupervised Network Representation Learning Framework on Node Classification Tasks

Mathematics, 2021
Network representation learning aims to learn low-dimensional, compressible, and distributed representational vectors of nodes in networks. Due to the expensive costs of obtaining label information of nodes in networks, many unsupervised network ...
Xin Xu, Yang Lu, Yupeng Zhou, Zhiguo Fu, Yanjie Fu, Minghao Yin   +5 more
doaj   +1 more source

Phosphatidylinositol 4‐kinase as a target of pathogens—friend or foe?

FEBS Letters, EarlyView.
This graphical summary illustrates the roles of phosphatidylinositol 4‐kinases (PI4Ks). PI4Ks regulate key cellular processes and can be hijacked by pathogens, such as viruses, bacteria and parasites, to support their intracellular replication. Their dual role as essential host enzymes and pathogen cofactors makes them promising drug targets.
Ana C. Mendes, Guilherme M. Azevedo, Amanda P. Barcellos, Diana Bahia   +3 more
wiley   +1 more source