Results 61 to 70 of about 14,201 (266)

Inpatient Exposure, Confidence, and Knowledge in Pediatric Hematology/Oncology: Evaluating General Pediatric Residents During 2025 ACGME Curriculum Change

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background General pediatricians often evaluate hematologic and oncologic presentations before subspecialty consultation, yet the 2025 Accreditation Council for Graduate Medical Education (ACGME) pediatric requirements reduce inpatient pediatric hematology/oncology (PHO) time, raising questions about resident readiness.
Colburn Yu, Rohini Jain
wiley   +1 more source

Study on Graph Collaborative Filtering Model Based on FeatureNet Contrastive Learning [PDF]

Jisuanji kexue
Graph-based collaborative filtering recommendation techniques have gained significant attention for their ability to efficiently process large-scale interaction data.However,the effectiveness of these techniques is limited by the sparsity of data in real-
WU Pengyuan, FANG Wei
doaj   +1 more source

Graph Communal Contrastive Learning

Proceedings of the ACM Web Conference 2022, 2022
Graph representation learning is crucial for many real-world applications (e.g. social relation analysis). A fundamental problem for graph representation learning is how to effectively learn representations without human labeling, which is usually costly and time-consuming. Graph contrastive learning (GCL) addresses this problem by pulling the positive
Bolian Li, Baoyu Jing, Hanghang Tong
openaire   +2 more sources

Change in Mental Health and Resilience in Childhood Cancer Survivors After Attending a Person‐Centred State‐of‐the‐Art Late Effects Clinic—on Behalf of the PanCareFollowUp Consortium

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Person‐centred follow‐up care based on evidence‐based clinical practice guidelines and providing individualised information should help to inform and reassure survivors about their medical and psychosocial situation and provide treatment and support where needed.
Gisela Michel, Mieke Rijken, Marietta Kokla, Charlotte Sleurs, Jurgen Lemiere, Line Elmerdahl Frederiksen, Luzius Mader, Cecilia Follin, Sara Oberti, Jeanette Falck Winther, Selina R. van den Oever, Leontien C. M. Kremer, Helena J. H. van der Pal, Peter Spreeuwenberg, Eline Bouwman, Jeroen te Dorsthorst, Samira Essiaf, Elizabeth A. M. (Lieke) Feijen, Hannah Gsell, Riccardo Haupt, Maria van Helvoirt, Rosella P. M. G. Hermens, Lars Hjorth, Tomas Kepak, Katerina Kepakova, Anita Kienesberger, Monica Muraca, Marleen Renard, Carina Schneider, Roderick Skinner, Anne Uyttebroeck, Deveny Vanrusselt, Sabine Verschueren, Jacqueline Loonen, Saskia M. F. Pluijm, Katharina Roser, the PanCareFollowUp consortium   +36 more
wiley   +1 more source

Forecasting the Dialysis Burden in Japan: Validation‐Based Projections of Prevalence and Incidence Through 2050

Therapeutic Apheresis and Dialysis, EarlyView.
ABSTRACT Background Japan has one of the highest dialysis prevalence rates worldwide and a shrinking, aging population. Whether dialysis burden has entered a sustained post‐peak phase or whether recent declines partly reflect pandemic‐related disruptions remains uncertain.
Hatice Şahin, Berrak Itır Aylı, Nüket Paksoy   +2 more
wiley   +1 more source

PDCNet: A Polarimetric Data-Enhanced Contrastive Learning Network for PolSAR Land Cover Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) has rich polarization information, offering an efficient and reliable means of collecting information. However, how to effectively leverage these complex data to extract polarization features remains a key ...
Bo Ren, Chaoyue Hua, Biao Hou, Jian Lv, Chen Yang, Licheng Jiao, Jocelyn Chanussot   +6 more
doaj   +1 more source

Graph Contrastive Learning for Materials

CoRR, 2022
Recent work has shown the potential of graph neural networks to efficiently predict material properties, enabling high-throughput screening of materials. Training these models, however, often requires large quantities of labelled data, obtained via costly methods such as ab initio calculations or experimental evaluation.
Teddy Koker, Keegan Quigley, Will Spaeth, Nathan C. Frey, Lin Li   +4 more
openaire   +2 more sources

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Investigating Contrastive Pair Learning’s Frontiers in Supervised, Semisupervised, and Self-Supervised Learning

Journal of Imaging
In recent years, contrastive learning has been a highly favored method for self-supervised representation learning, which significantly improves the unsupervised training of deep image models. Self-supervised learning is a subset of unsupervised learning
Bihi Sabiri, Amal Khtira, Bouchra El Asri, Maryem Rhanoui   +3 more
doaj   +1 more source

Graph Clustering with High-Order Contrastive Learning

Entropy, 2023
Graph clustering is a fundamental and challenging task in unsupervised learning. It has achieved great progress due to contrastive learning. However, we find that there are two problems that need to be addressed: (1) The augmentations in most graph ...
Wang Li, En Zhu, Siwei Wang, Xifeng Guo
doaj   +1 more source