Results 191 to 200 of about 8,068,929 (298)

Fisher Information Based Meteorological Factors Introduction and Features Selection for Short-Term Load Forecasting. [PDF]

Entropy (Basel), 2018
Cai S, Liu L, Sun H, Yan J.
europepmc   +1 more source

Distinct Systemic Sclerosis Phenotypes Related to Ethnicity: An Opportunity to Personalize Care?

Arthritis Care &Research, EarlyView.
Objective The objective is to describe and compare demographic, clinical, and serological characteristics of patients with systemic sclerosis (SSc) according to ethnic background. Methods Participants enrolled in the Canadian Scleroderma Research Group cohort who self‐identified to a single ethnicity group were included.
Danick Goulet, Camille Guertin, Maggie Larché, Isabelle Ferdinand, Marie Hudson, May Y. Choi, Mohammed Osman, Janet Pope, Carter Thorne, Murray Baron, Sasha Bernatsky, Sabrina Hoa   +11 more
wiley   +1 more source

Predictive models for short-term load forecasting in the UK's electrical grid. [PDF]

PLoS One
Sha'aban YA.
europepmc   +1 more source

Real‐World Safety and Effectiveness of JAK Inhibitors in Systemic Sclerosis: A Propensity‐Matched Study From the EUSTAR Cohort

Arthritis Care &Research, EarlyView.
Objective JAK inhibitors (JAKi) have shown promising effects in early‐phase studies of systemic sclerosis (SSc). We aimed to assess the safety and explore the effectiveness of JAKi compared to conventional immunosuppressants in SSc. Methods A longitudinal retrospective study of the European Scleroderma Trials and Research Group (EUSTAR) cohort was ...
Stefano Di Donato, Marie‐Elise Truchetet, Marco Minerba, Oliver Distler, Juan José Alegre Sancho, Yolanda Braun‐Moscovici, Christina Bergmann, Petros Sfikakis, Jeska K. de Vries‐Bouwstra, Murray Baron, Silvia Bellando‐Randone, Lorenzo Dagna, Christopher P. Denton, Madelon C. Vonk, Vanessa Smith, Ivan Castellvi, Gabriela Riemekasten, Andra Balanescu, Masataka Kuwana, Maria De Santis, Kamal Solanki, Anastas Batalov, Vahan Mukuchyan, Marco Matucci‐Cerinic, Yannick Allanore, Francesco Del Galdo, Michael Hughes, EUSTAR Collaborators   +27 more
wiley   +1 more source

REDf: a deep learning model for short-term load forecasting to facilitate renewable integration and attaining the SDGs 7, 9, and 13. [PDF]

PeerJ Comput Sci
Miah MSU, Sulaiman J, Islam MI, Masuduzzaman M, Lipu MSH, Nugraha R.   +5 more
europepmc   +1 more source

Engagement Patterns With an Artificial Intelligence Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, EarlyView.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data. [PDF]

Sci Rep
Zhou S, Zhang Q, Xiao P, Xu B, Luo G.
europepmc   +1 more source

Improved Neural Networks with Random Weights for Short-Term Load Forecasting. [PDF]

PLoS One, 2015
Lang K, Zhang M, Yuan Y.
europepmc   +1 more source

Longitudinal Changes in Adiposity After a Youth Sport‐Related Knee Injury: Informing Posttraumatic Osteoarthritis Prevention

Arthritis Care &Research, EarlyView.
Objective Youth who experience a sport‐related knee injury have elevated odds of becoming overweight or developing obesity in 3 to 10 years, compounding their risk for posttraumatic osteoarthritis (PTOA). To inform prevention strategies, this study compared patterns of adiposity change between youth with a sport‐related knee injury and uninjured youth ...
Justin M. Losciale, Nuria E. J. Jansen, Christina Y. Le, Leo Lu, Hui Xie, Marienke van Middelkoop, Jackie L. Whittaker   +6 more
wiley   +1 more source

Deep learning-driven hybrid model for short-term load forecasting and smart grid information management. [PDF]

Sci Rep
Wen X, Liao J, Niu Q, Shen N, Bao Y.
europepmc   +1 more source