Results 51 to 60 of about 273,034 (301)

Combining graph neural networks and spatio-temporal disease models to improve the prediction of weekly COVID-19 cases in Germany

Scientific Reports, 2022
During 2020, the infection rate of COVID-19 has been investigated by many scholars from different research fields. In this context, reliable and interpretable forecasts of disease incidents are a vital tool for policymakers to manage healthcare resources.
Cornelius Fritz, Emilio Dorigatti, David Rügamer   +2 more
doaj   +1 more source

Computing Multi-Relational Sufficient Statistics for Large Databases [PDF]

, 2014
Databases contain information about which relationships do and do not hold among entities. To make this information accessible for statistical analysis requires computing sufficient statistics that combine information from different database tables. Such
Qian, Zhensong, Schulte, Oliver, Sun, Yan   +2 more
core   +1 more source

Statistical learning creates novel object associations via transitive relations [PDF]

Journal of Vision, 2016
A remarkable ability of the cognitive system is to make novel inferences on the basis of prior experiences. What mechanism supports such inferences? We propose that statistical learning is a process through which transitive inferences of new associations are made between objects that have never been directly associated.
Yu Luo, Jiaying Zhao
openaire   +3 more sources

Evaluation of a novel EHR sidecar application to display RA clinical outcomes during clinic visits: results of a stepped‐wedge cluster randomized pragmatic trial

Arthritis Care &Research, Accepted Article.
Objective We developed a novel EHR sidecar application to visualize key rheumatoid arthritis (RA) outcomes, including disease activity, physical function, and pain, via a patient‐facing graphical interface designed for use during outpatient visits (“RA PRO dashboard”).
Gabriela Schmajuk, Jing Li, Cathy Nasrallah, Cherish Wilson, Alicia Hamblin, Christine Hariz, Cammie Young, Stephen Shiboski, Emma Kersey, Mary Nakamura, Judith F. Ashouri, Mehrdad Matloubian, Andrew J. Gross, Jennifer Barton, Beth Berrean, Jonathan Prugh, Jinoos Yazdany   +16 more
wiley   +1 more source

Lifted graphical models: a survey [PDF]

, 2015
Lifted graphical models provide a language for expressing dependencies between different types of entities, their attributes, and their diverse relations, as well as techniques for probabilistic reasoning in such multi-relational domains. In this survey,
Angelika Kimmig, B Ahmadi, B London, BL Richards, C Yanover, CM Bishop, D Heckerman, D Heckerman, D Koller, D Poole, D Suciu, EM Airoldi, FR Kschischang, H Khosravi, HR Lourenço, J Besag, J Neville, J Pearl, J Pearl, JR Quinlan, L Getoor, L Getoor, L Raedt De, L Raedt De, L Raedt De, L Raedt De, L Tierney, Lilyana Mihalkova, Lise Getoor, LR Rabiner, M Otterlo Van, M Richardson, MJ Wainwright, MP Wellman, N Lavrac̆, N Taghipour, O Schulte, O Schulte, P Damien, P Domingos, P Sen, P Spirtes, R Salvo Braz de, R Salvo Braz de, S Macskassy, S Muggleton, S Muggleton, S Natarajan   +47 more
core   +1 more source

Statistical relational learning for workflow mining

Intelligent Data Analysis, 2016
The management of business processes can support efficiency improvements in organizations. One of the most interesting problems is the mining and representation of process models in a declarative language. Various recently proposed knowledge-based languages showed advantages over graph-based procedural notations.
BELLODI, Elena, RIGUZZI, Fabrizio, LAMMA, Evelina   +2 more
openaire   +2 more sources

Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re‐Usability: A Position Paper From the Nanosafety Community

Advanced Sustainable Systems, EarlyView.
Nanosafety data provide a guiding example for establishing best practices in data management, aligning with FAIR principles and quality criteria. This review explores existing quality assessment approaches for reliability, relevance, and completeness, emphasizing the need for harmonization and adaptation to nanomaterials and advanced materials. The aim
Verónica I. Dumit, Irini Furxhi, Penny Nymark, Antreas Afantitis, Ammar Ammar, Monica J. B. Amorim, Dalila Antunes, Svetlana Avramova, Chiara L. Battistelli, Gianpietro Basei, Cecilia Bossa, Emil Cimpan, Mihaela Roxana Cimpan, Dmitri Ciornii, Anna Costa, Camilla Delpivo, Maria Dusinska, Ana Sofia Fonseca, Steffi Friedrichs, Vasile‐Dan Hodoroaba, Danail Hristozov, Panagiotis Isigonis, Nina Jeliazkova, Nikolay Kochev, Eva Kranjc, Dieter Maier, Georgia Melagraki, Anastasios G. Papadiamantis, Tomasz Puzyn, Hubert Rauscher, Katie Reilly, Araceli Sánchez Jiménez, Janeck J. Scott‐Fordsmand, Neeraj Shandilya, Hyun Kil Shin, Gergana Tancheva, Jeaphianne P. M. van Rijn, Egon L. Willighagen, Ewelina Wyrzykowska, Martine I. Bakker, Damjana Drobne, Thomas E. Exner, Martin Himly, Iseult Lynch   +43 more
wiley   +1 more source

Improving Data Quality by Leveraging Statistical Relational\ud Learning [PDF]

, 2016
Digitally collected data su\ud ↵\ud ers from many data quality issues, such as duplicate, incorrect, or incomplete data. A common\ud approach for counteracting these issues is to formulate a set of data cleaning rules to identify and repair incorrect ...
Akbik, A, Kaul, M, Markl, V, Rabl, T, Visengeriyeva, L   +4 more
core   +2 more sources

A Novel Hybrid Temporal Fusion Transformer Graph Neural Network Model for Stock Market Prediction

AppliedMath
Forecasting stock prices remains a central challenge in financial modelling, as markets are influenced by market sentiment, firm-level fundamentals and complex interactions between macroeconomic and microeconomic factors, for example.
Sebastian Thomas Lynch, Parisa Derakhshan, Stephen Lynch   +2 more
doaj   +1 more source

Multiomics Analyses Reveal an Essential Role of Tryptophan in Treatment of csDMARDs in Rheumatoid Arthritis

Advanced Science, EarlyView.
Rheumatoid arthritis is a disease characterized by joint inflammation. Approximately 50% of patients show insufficient response to traditional synthetic disease‐modifying antirheumatic drugs. This study aims to elucidate differential molecular profiles of the mechanisms underlying drug responses through multi‐omics strategy.
Congcong Jian, Jing Zhu, Jianhong Wu, Yan Zhang, Jianghua Chen, Huan Wang, Hengyan Liu, Ke Xu, Jiaxin Huang, Xiaoting Zhu, Yuanli Wei, Shilin Li, Tingting Wang, Xuan Huang, Qinghua Zou, Jie Zhang, Jiang Su, Xinming Du, Yaping Lu, Tianci Zhou, Yingtong Zhou, Minglong Tang, Bin Li, Xue Zhou, Qihao Wei, Qiulong Yan, Fanxin Zeng   +26 more
wiley   +1 more source