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 ...
A river plume indicates the dispersion and transport path of pollutants from runoff, monitoring the spatiotemporal variation of river plume distribution from space is crucial for marine environmental governance. This study focuses on the Pearl River ...
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.
RATIONALE AND OBJECTIVES: To develop an interpretable machine learning (ML) model based on cardiac magnetic resonance (CMR) multimodal parameters and clinical data to discriminate Takotsubo syndrome (TTS), acute myocardial infarction (AMI), and acute...
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...
BACKGROUND: Determining whether pediatric patients with low-grade gliomas (pLGGs) have tumor-related epilepsy (GAE) is a crucial aspect of preoperative evaluation. Therefore, we aim to propose an innovative, machine learning- and deep learning-based ...
Journal of minimally invasive gynecology
Sep 1, 2025
OBJECTIVE: To evaluate the predictive value of clinical features in the diagnosis of endometriosis by utilizing machine learning algorithms (MLAs), aiming to develop an accurate, explainable prediction model.
While machine learning has gained traction in toxicological assessments, the limited data availability requires the quantification of uncertainty of in silico predictions for reliable decision-making. This study addresses the challenge of predicting ...
Journal of molecular graphics & modelling
Sep 1, 2025
The total polar surface area (TPSA) is a crucial parameter in photovoltaic (PV) materials, as it directly influences their solubility, processability, and device performance. This study leverages machine learning-assisted reverse engineering to gener...
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