Results 211 to 220 of about 87,394 (276)
Objective Targeted therapies for facioscapulohumeral muscular dystrophy (FSHD) are progressing through clinical trials. Electrical impedance myography (EIM) provides a noninvasive biomarker of muscle composition that may be valuable especially in early phase trials. This study evaluated EIM data from a multicenter FSHD cohort over 24 months.
Karlien Mul +15 more
wiley +1 more source
Universal feature selection for simultaneous interpretability of multitask datasets. [PDF]
Raymond M +3 more
europepmc +1 more source
Objective The extent of neuronal loss in Parkinson's disease (PD) and the pathogenic processes underlying neuronal dysfunction and loss remain poorly understood. Here, we analyzed the expression of key molecules representing different cell death signaling pathways and their association with Lewy pathology, dopaminergic (DA) neuron loss and stage of PD ...
Yue Jing Heng +3 more
wiley +1 more source
Identifying optimal locations for automated external defibrillators (AED) in Freiburg: development and validation of a machine learning model based on demographic and infrastructural data. [PDF]
Ganter J +10 more
europepmc +1 more source
DT-aided resource allocation via generative adversarial imitation learning in complex cloud-edge-end scenarios. [PDF]
Zhang X, Xin M, Li Y, Fu Q.
europepmc +1 more source
Inferring effective networks of spiking neurons using a continuous-time estimator of transfer entropy. [PDF]
Shorten DP +3 more
europepmc +1 more source
ABSTRACT To address the issues of neglecting the spatiotemporal correlations among process variables, low‐level features are vulnerable to noise interference, and the gradual loss of key information layer by layer during deep network training in traditional stacked autoencoder‐based soft‐sensor models, this paper proposes a hierarchical complementary ...
Xiaoping Guo, Jinghong Guo, Yuan Li
wiley +1 more source
Advancing Structure Elucidation with a Flexible Multi-Spectral AI Model. [PDF]
Priessner M +6 more
europepmc +1 more source
Toward Solution‐Time Advantage With Error‐Mitigated Quantum Annealing for Combinatorial Optimization
This paper presents a novel error mitigation technique to address the qubit errors that occur when solving combinatorial optimization problems with quantum annealing. The approach significantly speeds up the computation to reach the global optimum solution for a correlated 3D image segmentation model for material microstructures, demonstrating a ...
Yushuang Sam Yang +3 more
wiley +1 more source

