Results 71 to 80 of about 1,303,019 (294)

Network Localization of Fatigue in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Fatigue is among the most common symptoms and one of the main factors determining the quality of life in multiple sclerosis (MS). However, the neurobiological mechanisms underlying fatigue are not fully understood. Here we studied lesion locations and their connections in individuals with MS, aiming to identify brain networks ...
Olli Likitalo, Jaakko Kungshamn, Albert Bellmunt‐Gil, Silvia Tommasin, Abhineet Ojha, Matias Viitala, Juho Aaltonen, Jyrki Lötjönen, Juha Koikkalainen, Pauli Ylikotila, Patrizia Pantano, Merja Soilu‐Hänninen, Juho Joutsa   +12 more
wiley   +1 more source

Analysis of Mixed Outcomes: Misclassified Binary Responses and Measurement Error in Covariates [PDF]

The focus of this paper is on regression models for mixed binary and continuous outcomes, when the true predictor is measured with error and the binary responses are subject to classification errors.
Banerjee, Tathagata, Roy Surupa
core  

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

Estimation and Statistical Test in Bivariate Binary Probit Model

Jurnal Ilmu Dasar, 2012
One of the models that can be used to analyze two binary response variables data is bivariate binary probit model. This paper tried to estimate the parameters of bivariate binary probit model using Maximum Likelihood Estimationmethod, whereastoget the ...
Vita Ratnasari, Purhadi Purhadi, Ismaini Ismaini, Suhartono Suhartono   +3 more
doaj  

Demand Response Control of Beverage Production Plants With Binary Units

IEEE Access
This paper explores two main optimal control strategies to utilize the production flexibility potentials of beverage production lines for ancillary service provision.
Behzad Heydaryan, Mohammad Al Khatib, Naim Bajcinca   +2 more
doaj   +1 more source

The Dirichet-Multinomial model for multivariate randomized response data and small samples [PDF]

, 2012
In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when ...
Avetisyan, M., Fox, G.J.A.
core   +1 more source

Fundamentals of the TianQin mission

, 2015
This talk adds more detail to the proposed TianQin mission \cite{TQ}. The response of TianQin to a binary source is an important problem for the experiment.
Mei, Jianwei, Shao, Chenggang, Wang, Yan
core   +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

Randomized Response and the Binary Probit Model [PDF]

The paper analyzes eects of randomized response with respect to some binary dependent variable on the estimation of the probit model. This approach is used in interviews when asking sensitive questions.
Gerd Ronning
core  

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source