Results 191 to 200 of about 537,336 (309)

DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction. [PDF]

Sci Rep
GulMohamed RB, Hetany W, Almaimani HA, Khiery FAS.   +3 more
europepmc   +1 more source

Frailty Exacerbates Disability in Progressive Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background To evaluate frailty in severe progressive multiple sclerosis (PMS) and to investigate the underlying mechanisms. Methods This prospective, cross‐sectional, multicenter study enrolled a late severe PMS group requiring skilled nursing (n = 53) and an age, sex, and disease duration‐matched control PMS group (n = 53).
Taylor R. Wicks, Anna Wolska, Diala Ghazal, Dejan Jakimovski, Bianca Weinstock‐Guttman, Alexander Burnham, Niels Bergsland, Michael G. Dwyer, Alan T. Remaley, Robert Zivadinov, Murali Ramanathan   +10 more
wiley   +1 more source

New methods for multivariate distribution forecasting

, 2019
This thesis contributes to the current literature in finance and economics by introducing new methods for forecasting and accuracy evaluation. First, we propose and develop a new multivariate distribution forecasting method. Second, we compare proper scoring rules through a discrimination measure.
openaire  

Fibrinogen Changes Before and After Intravenous Thrombolysis as Predictors of Cerebral Injury and Clinical Outcomes in Acute Ischemic Stroke: A Multicenter Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Plasma fibrinogen is essential in thrombosis and fibrinolysis, yet its dynamic changes pre‐ and post‐intravenous thrombolysis (IVT) for predicting brain injury severity and prognosis in acute ischemic stroke (AIS) patients remain unclear.
Wenhai Zhai, Yang Qu, Reziya Abuduxukuer, Kejia Zhang, Peng Zhang, Xin Tang, Huaimei Zhang, Lijuan Wang, Lichong Yang, Shuangxu Tan, Zhimei Yuan, Ce Han, Lili He, Yuping Zheng, Fenglan Zhao, Lijie Guo, Ligang Jiang, Jinfeng Li, Yongfei Jiang, Xuexia Zou, Dan Xu, Han Xu, Xiaojia Wang, Yingbin Qi, Xuefeng Hu, Yu Zhang, Zhen‐Ni Guo, Hang Jin, on behalf of the Biomarkers of Brain Injury Investigator Study Group   +28 more
wiley   +1 more source

A machine learning-based short-term forecasting method for heavy fog in Anhui Province of China. [PDF]

Sci Rep
Sun Y, Wang C, Yao Y, Wang F, Zhou J, Wang X.   +5 more
europepmc   +1 more source

Inhibition of Classical and Alternative Complement Pathway by Ravulizumab and Eculizumab

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore the feasibility of classical (CH50) and alternative (AH50) complement pathway activity as potential biomarkers for treatment guidance and monitoring during therapy with ravulizumab in patients with generalized myasthenia gravis (gMG) and compare these to therapeutic drug monitoring under eculizumab.
Lea Gerischer, Frauke Stascheit, Maximilian Mönch, Paolo Doksani, Carla Dusemund, Meret Herdick, Philipp Mergenthaler, Maike Stein, Amani Suboh, Jutta Schröder‐Braunstein, Guido Wabnitz, Jan D. Lünemann, Sophie Lehnerer, Sarah Hoffmann, Andreas Meisel   +14 more
wiley   +1 more source

UniEload: Electrical load dataset for energy forecasting applications at public universities in Bangladesh. [PDF]

Data Brief
Sutradhar U, Biswas P, Hossain S, Islam ATMS, Dev S.   +4 more
europepmc   +1 more source

Changes in Immune‐Inflammation Status and Acute Ischemic Stroke Prognosis in Prospective Cohort

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Inflammation is a critical risk factor for poor outcomes in cerebral infarction. Prior studies focused primarily on baseline inflammation status, neglecting dynamic longitudinal changes. We try to investigate the association between immune‐inflammation status alterations and stroke prognosis, and evaluated three systemic biomarkers'
Songfang Chen, Wenting Huang, Yitian Liu, Xuan Chen, Buyu Ke, Qian Shen, Hanyu Cai, Jing Sun, Yan Li, Yungang Cao, Beilei Hu, Keyang Chen   +11 more
wiley   +1 more source

Seasonal forecasting using the GenCast probabilistic machine learning model. [PDF]

Clim Dyn
Antonio B, Strommen K, Christensen HM.
europepmc   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source