BACKGROUND: Substantial gaps exist in the neuroprognostication of cardiac arrest patients who remain comatose after the restoration of spontaneous circulation. Most studies focus on predicting survival, a measure confounded by the withdrawal of life-...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Estimating the individuals' potential response to varying treatment doses is crucial for decision-making in areas such as precision medicine and management science. Most recent studies predict counterfactual outcomes by learning a covariate represent...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Monocular depth estimation (MDE) has long been a popular and challenging task. Currently, mainstream methods mainly include regression methods based on geometric constraints and ordinal regression methods based on discretized depth intervals. However...
High-resolution magnetic resonance angiography (∼ 50 μm MRA) data plays a critical role in the accurate diagnosis of various vascular disorders. However, it is very challenging to acquire, and it is susceptible to artifacts and noise which limits its...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
This paper presents the D-type distributed iterative learning control protocol to synchronize fractional-order competitive neural networks with time delay within a finite time frame. Firstly, the input sharing strategy of such desired competitive neu...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Linear discriminant analysis (LDA) is a dimensionality reduction method appreciated by many researchers in the field of machine learning. LDA is usually summarized as a trace ratio problem: minTr(WSW)/Tr(WSW), which has clear physical meaning but is ...
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Polyp segmentation is critical in medical image analysis. Traditional methods, while capable of producing precise outputs in well-defined regions, often struggle with blurry or ambiguous areas in medical images, which can lead to errors in clinical d...
Accurate forecasting of algal blooms is essential for implementing timely control measures. However, given their inherent complex time-frequency characteristics, capturing the dynamics of algal blooms remains an ongoing challenge in standalone models...
BJOG : an international journal of obstetrics and gynaecology
Sep 1, 2025
OBJECTIVE: To create and validate a machine learning (ML)-based model for predicting the adverse perinatal outcome (APO) in foetal growth restriction (FGR) at diagnosis.
Neural networks : the official journal of the International Neural Network Society
Sep 1, 2025
Network embedding, an effective method for learning low-dimensional representations of nodes, plays a crucial role in various network learning scenarios. However, existing network embedding learning methods fail to learn node embeddings from the pers...
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