Results 111 to 120 of about 332,886 (299)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller +14 more
wiley +1 more source
MapReduce for Bayesian Network Parameter Learning using the EM Algorithm
, 2018 This work applies the distributed computing framework MapReduce to Bayesian network parameter learning from incomplete data. We formulate the classical Expectation Maximization (EM) algorithm within the MapReduce framework.
Aniruddha Basak (4940215) +2 more
core +1 more source
Iterative Learning Control for MIMO Singular Distributed Parameter Systems
IEEE Access, 2017 This paper deals with the iterative learning control issue for multi-input multi-output singular distributed parameter systems (SDPSs) with parabolic and hyperbolic type, which described by coupled partial differential equations with singular matrix ...
Xi-Sheng Dai +3 more
doaj +1 more source
PSR: Unified Framework of Parameter-Learning-Based MR Image Superresolution. [PDF]
J Healthc Eng, 2021 Liu H, Liu J, Li J, Pan JS, Yu X.
europepmc +1 more source
Learning about the Parameter of the Bernoulli Model
Journal of Computer and System Sciences, 1997 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +1 more source
Uncovering G Protein‐Coupled Receptors: Novel Targets and Biomarkers for Predicting Glioma Prognosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Low‐grade gliomas (LGG) exhibit significant heterogeneity and recurrence risk. G protein‐coupled receptors (GPCR) contribute to glioma malignant progression, but their prognostic value remains unclear. This work attempts to formulate a GPCR‐based outcome‐predicting model for LGG. Methods Based on TCGA LGG data, the enrichment scores
Jun Yang +4 more
wiley +1 more source
, 2018 Dynamical systems are a natural and convenient way to model the evolution of processes observed in practice. When uncertainty is considered and incorporated, these system become known as stochastic dynamical systems.
Dass, Sarat C.; id_orcid +5 more
core +1 more source
QoS-Aware State-Augmented Learning for Wireless Coexistence Parameter Management
IEEE Transactions on Machine Learning in Communications and NetworkingEfficient and fair coexistence in unlicensed spectrum is critical for next-generation wireless networks such as 5G New Radio in Unlicensed Spectrum (NR-U) and Wi-Fi, which contend for shared resources under diverse Quality of Service (QoS) requirements ...
Mohammad Reza Fasihi +2 more
doaj +1 more source
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Structure and parameter learning algorithms for fuzzy neural network systems
, 1992 A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed for the realization of a fuzzy logic control and decision system.
Lin, Chin-Teng
core