Results 121 to 130 of about 17,286,028 (305)

Early Clinical and Cerebrospinal Fluid Predictors of 1‐Year Recurrence in Autoimmune GFAP Astrocytopathy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Autoimmune glial fibrillary acidic protein astrocytopathy (GFAP‐A) is an inflammatory central nervous system disorder with variable outcomes. Relapse occurs in a subset of patients, but early predictors remain unclear. We aimed to identify admission‐available features associated with 1‐year recurrence and develop an interpretable ...
Qingting Hong, Yuping Xiao, Yuhan Wu, Ziyuan Huang, Weishan Liang, Li Xiao, Yaqing Shu, Tingting Lu, Yanyu Chang, Wei Qiu, Yuge Wang   +10 more
wiley   +1 more source

Accelerating coral rubble instability assessments with machine learning: insights from the Great Barrier Reef

Applied Ocean Research
The stability of coral rubble is crucial for coral reef recovery since a stable coral rubble base is essential for coral regeneration. To enhance the effectiveness of coral reef restoration and to model the recovery and connectivity of coral reef ...
Dongfang Liu, David P. Callaghan, Tom E. Baldock   +2 more
doaj   +1 more source

Random Forest model performance on synthetic training data.

, 2019
Random Forest model performance on synthetic training data.
Ines Levin (5004560), R. Michael Alvarez (4237378), Mali Zhang (7610306)   +2 more
core   +1 more source

Anticoagulation Treatment Response Among Phenotypic ESUS Clusters: Evidence From CASPR

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate treatment effect heterogeneity across phenotypic clusters of patients with cryptogenic embolic stroke using causal inference methods. Methods From a retrospective, multicenter cohort of patients with cryptogenic embolic stroke, we estimated the treatment effect of anticoagulation versus antiplatelet therapy in patients ...
Elena Badillo Goicoechea, Patrick Ellsworth, James E. Siegler, James R. Brorson, Christina M. Lineback, Frank G. Conyers, Deborah Kerrigan, Kelsey Eklund, Shadi Yaghi, Farid Khasiyev, Emiliya Melkumova, Collin J. Culbertson, Marissa D'Souza, Dinesh V. Jillella, Patrick Glover, Hassan Aboul‐Nour, Fadi Nahab, Mahan Shahrivari, Simona Nedelcu, David S. Liebeskind, Matthew M. Smith, Aaron Rothstein, Anna Bowman, Alicia Zha, Narendra Kala, Ahmad Abu Qdais, Sami Al Kasab, Mudassir Farooqui, Diana Rojas‐Soto, Yasmin Aziz, Franziska Herpich, Jean‐Philippe Daniel, Sean L. Thompson, Vivek Patel, Thanh N. Nguyen, Siddharth Sehgal, Wenzheng Yu, Wayneho Kam, Russel Van Coevering, Oana M. Dumitrascu, Muhammad Alvi, Balaji Krishnaiah, Setareh Salehi Omran, Guillermo Linares, Eesha Singh, Hamid Ali, Mary Penckofer, Jesse M. Thon, Shani Mannion, Dalia Chahien, Lucia Chen, Fawad Talat, Mehdi Abbasi, Richa Sharma   +53 more
wiley   +1 more source

Serostatus‐Specific Prognostic Profiles and Phenotype‐Dependent Therapeutic Windows in Autoimmune Encephalitis: A Multicenter Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background While autoimmune encephalitis (AE) outcomes vary, serostatus‐specific prognostic determinants and institutional clustering effects remain poorly characterized. We aimed to delineate the distinct prognostic architecture of AE, identifying serostatus‐specific risk factors and potential therapeutic windows.
Xiaohong Tang, Jingxian Wang, Kaixin Zhu, Zhen Zhang, Liao Wu, Wei Wang, Chang Li, Qingyun Li, Hao Li, Jinghua Chen, Zhangxu Lian, Bin Liu, Tengfei Liu, Chunmei Wen, Nuan Wang, Sen Qun, Lishun Xiao, Qingwei Lai   +17 more
wiley   +1 more source

L1-based compression of random forest models.

, 2012
Random forests are effective supervised learning methods applicable to large-scale datasets. However, the space complexity of tree ensembles, in terms of their total number of nodes, is often prohibitive, specially in the context of problems with very high-dimensional input spaces.
Joly, Arnaud, Schnitzler, François, Geurts, Pierre, Wehenkel, Louis   +3 more
openaire   +2 more sources

Navigating Random Forests and related advances in algorithmic modeling [PDF]

Statistics Surveys, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Modified random forest regression model for predicting wholesale rice prices

, 2023
Modified random forest regression model for predicting wholesale rice ...
GSK Prasatya (18977966), SOB Widiarto (18977972), HJ Christanto (18977969), C Dewi (13596229), G Dai (13674820)   +4 more
core  

Individuals With Multijoint Osteoarthritis Demonstrate Larger Longitudinal Declines in Frailty: Data From the Canadian Longitudinal Study on Aging

Arthritis Care &Research, EarlyView.
Objective The aim of this study was to test the hypothesis that multijoint osteoarthritis would modify the relation between time and frailty progression, in which more affected joints would lead to larger declines over six years compared to those without osteoarthritis using data from the Canadian Longitudinal Study on Aging.
Carson Halliwell, Rebecca Moyer, Myles W. O'Brien   +2 more
wiley   +1 more source