Results 61 to 70 of about 6,993,713 (204)

Contrastive cross-domain sequential recommendation with attention-aware mechanism

Complex & Intelligent Systems
Cross-domain sequential recommendation (CDSR) aims to predict future sequential interactions in a target domain by analyzing historical sequence data from different domains.
Wei Zhao, Bo Li, Xian Mo
doaj   +1 more source

Digital Cognitive Phenotyping for Differential Diagnosis and Monitoring in Neurological Conditions

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To assess the utility, accessibility, and equivalence to supervised scales of online cognitive assessment in older individuals with cognitive impairment. Methods Patients with Alzheimer's disease (AD, n = 31), idiopathic normal pressure hydrocephalus (iNPH, n = 26), and traumatic brain injury (TBI, n = 23) completed online cognitive ...
Martina Del Giovane, Valentina Giunchiglia, Michael C. B. David, Magdalena A. Kolanko, William R. Trender, Peter J. Hellyer, Harmeena Kaur, David J. Sharp, Christopher Carswell, Paresh A. Malhotra, Adam Hampshire   +10 more
wiley   +1 more source

Gromov-Wasserstein Guided Representation Learning for Cross-Domain Recommendation

, 2022
Cross-Domain Recommendation (CDR) has attracted increasing attention in recent years as a solution to the data sparsity issue. The fundamental paradigm of prior efforts is to train a mapping function based on the overlapping users/items and then apply it
Wang, Zihao, Wu, Xian, Li, Xinhang, Qiu, Zhaopeng, Zhao, Xiangyu, Xing, Chunxiao, Zhang, Yong   +6 more
core   +1 more source

Factors Associated With the Rising Trend in Self‐Reported Cognitive Disability Among U.S. Adults Aged 18–39 From 2013–2024

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Building on our prior Behavioral Risk Factor Surveillance System analysis identifying adults aged 18–39 as the primary driver of the national increase in self‐reported cognitive disability, we examined factors associated with this rise using 2013–2024 U.S. BRFSS data. Methods We analyzed U.S.
Adam de Havenon, Ka‐Ho Wong, Mirriam Mananah, Christopher D. Anderson, Ada Fenick, Amy Arnsten, Arman Fesharaki‐Zadeh, James C. McPartland, Mary L. Adams, Kevin N. Sheth   +9 more
wiley   +1 more source

Mixed Attention Network for Cross-domain Sequential Recommendation [PDF]

, 2023
In modern recommender systems, sequential recommendation leverages chronological user behaviors to make effective next-item suggestions, which suffers from data sparsity issues, especially for new users.
Lin, Guanyu, Zheng, Yu, Niu, Yanan, Gai, Kun, Jin, Depeng, Li, Yong, Song, Yang, Wang, Meng, Chang, Jianxin, Li, Zhiheng, Gao, Chen   +10 more
core  

Temporal Interference Stimulation of Centromedian‐Parafascicular Complex in Disorders of Consciousness: A Pilot Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu, Changgeng Song, Dianwei Wu, Xiaoqian Niu, Jianmin Hao, Lijuan Liu, Xiaogang Kang, Wen Jiang   +7 more
wiley   +1 more source

Neural Attentive Cross-Domain Recommendation

, 2019
Nowadays, users open multiple accounts on social media platforms and e-commerce sites, expressing their personal preferences on different domains. However, users' behaviors change across domains, depending on the content that users interact with, such as
Fabio Crestani, Rafailidis, Dimitrios, Crestani, Fabio, Dimitrios Rafailidis   +3 more
core   +1 more source

Entity-relation pair attention-based representation with knowledge graph for media-content cross-domain recommendation

Complex & Intelligent Systems
With the popularity of Internet services and the explosive growth of information, recommendation algorithm have become increasingly crucial in the all-media era.
Tongtong Xing, Yuewei Wu, Ruiling Fu, Junyi Chen, Fulian Yin   +4 more
doaj   +1 more source

“Low‐Positive” MOG‐IgG Cases Among Adults With a First Event Suggestive of Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To determine the prevalence and clinical characteristics of patients with “low‐positive” (LP) MOG‐IgG (titres 1:160–1:320) among adults with a first demyelinating event (FDE) suggestive of multiple sclerosis (MS). Methods From the Barcelona CIS inception cohort, we included adult patients with serum collected ≤ 6 months from the FDE.
Javier Villacieros‐Álvarez, Carmen Espejo, Georgina Arrambide, Mireia Castillo, Marta Rodriguez, Helena Ariño, Iker Elosua, Carmen Tur, Angela Vidal‐Jordana, Andreu Vilaseca, Joaquín Castilló, Ingrid Galán, Luciana Midaglia, Carlos Nos, Breogan Rodríguez‐Acevedo, Ana Zabalza, Luca Bollo, Agustín Pappolla, René Carvajal, Neus Mongay‐Ochoa, Jordi Rio, Jaume Sastre‐Garriga, Manuel Comabella, Gesualdina Busiello, Sofia Sceppacuercia, Àlex Rovira, Xavier Montalban, Mar Tintoré, Cristina Auger, Álvaro Cobo‐Calvo   +29 more
wiley   +1 more source

Cross-Domain Recommendation Algorithm Based on Latent Factor Model

Dianxin kexue, 2015
In the internet environment，the combining of multi-source heterogeneous information objects in different areas makes users face information selection dilemma problem in big data environment.It has been very difficulty for traditional information ...
Sheng Gao, Siting Ren, Jun Guo
doaj   +2 more sources