Identifying and Reporting Dependent Adult abuse

Contrastive independent subspace analysis network for multi-view spatial information extraction.

Multi-view classification integrates features from different views to optimize classification performance. Most of the existing works typically utilize semantic information to achieve view fusion but neglect the spatial information of data itself, which accommodates data representation with correlation information and is proven to be an essential aspect. Thus robust independent subspace analysis n...

A universal strategy for smoothing deceleration in deep graph neural networks.

Graph neural networks (GNNs) have shown great promise in modeling graph-structured data, but the over-smoothing problem restricts their effectiveness in deep layers. Two key weaknesses of existing research on deep GNN models are: (1) ignoring the beneficial aspects of intra-class smoothing while focusing solely on reducing inter-class smoothing, and (2) inefficient computation of residual weights ...

Noninvasive identification of HER2 status by integrating multiparametric MRI-based radiomics model with the vesical imaging-reporting and data system (VI-RADS) score in bladder urothelial carcinoma.

PURPOSE: HER2 expression is crucial for the application of HER2-targeted antibody-drug conjugates. This study aims to construct a predictive model by ...

Machine learning assisted multi-signal nanozyme sensor array for the antioxidant phenolic compounds intelligent recognition.

Identifying antioxidant phenolic compounds (APs) in food plays a crucial role in understanding their biological functions and associated health benefi...

Development and validation of a support vector machine-based nomogram for diagnosis of obstetric antiphospholipid syndrome.

BACKGROUND: Antiphospholipid Syndrome (APS) is a systemic autoimmune disorder characterized by arterial or venous thrombosis and/or pregnancy complica...

Unsupervised Domain Adaptation for EM Image Denoising With Invertible Networks.

Electron microscopy (EM) image denoising is critical for visualization and subsequent analysis. Despite the remarkable achievements of deep learning-b...

Mapping Thrombosis Serum Markers by H-NMR Allied with Machine Learning Tools.

Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolis...

Counterfactual learning for higher-order relation prediction in heterogeneous information networks.

Heterogeneous Information Networks (HINs) play a crucial role in modeling complex social systems, where predicting missing links/relations is a signif...

QUAIDE - Quality assessment of AI preclinical studies in diagnostic endoscopy.

Artificial intelligence (AI) holds significant potential for enhancing quality of gastrointestinal (GI) endoscopy, but the adoption of AI in clinical ...

Learning soft tissue deformation from incremental simulations.

BACKGROUND: Surgical planning for orthognathic procedures demands swift and accurate biomechanical modeling of facial soft tissues. Efficient simulati...

AI-enabled clinical decision support tools for mental healthcare: A product review.

The review seeks to promote transparency in the availability of regulated AI-enabled Clinical Decision Support Systems (AI-CDSS) for mental healthcare...

Signed Curvature Graph Representation Learning of Brain Networks for Brain Age Estimation.

Graph Neural Networks (GNNs) play a pivotal role in learning representations of brain networks for estimating brain age. However, the over-squashing i...

Liver tumor segmentation method combining multi-axis attention and conditional generative adversarial networks.

In modern medical imaging-assisted therapies, manual annotation is commonly employed for liver and tumor segmentation in abdominal CT images. However,...

PDG2Seq: Periodic Dynamic Graph to Sequence Model for Traffic Flow Prediction.

Traffic flow prediction is the foundation of intelligent traffic management systems. Current methods prioritize the development of intricate models to...

Differentiating atypical parkinsonian syndromes with hyperbolic few-shot contrastive learning.

Differences in iron accumulation patterns have been observed in susceptibility-weighted images across different classes of atypical parkinsonian syndr...

Machine learning estimates on the impacts of detection times on wildfire suppression costs.

As climate warming exacerbates wildfire risks, prompt wildfire detection is an essential step in designing an efficient suppression strategy, monitori...

MRI denoising with a non-blind deep complex-valued convolutional neural network.

MR images with high signal-to-noise ratio (SNR) provide more diagnostic information. Various methods for MRI denoising have been developed, but the ma...

Development and validation of a prediction model for ED using machine learning: according to NHANES 2001-2004.

Erectile Dysfunction (ED) is a form of sexual dysfunction in males that imposes significant health and financial burdens globally. Despite its high pr...

Artificial intelligence algorithms enhance urine cytology reporting confidence in postoperative follow-up for upper urinary tract urothelial carcinoma.

PURPOSE: In Taiwan, the incidence of urothelial carcinoma of the upper urinary tract (UTUC) is high and intravesical recurrence is approximately 22%-4...

ChatGPT and radiology report: potential applications and limitations.

Large language models like ChatGPT, with their growing accessibility, are attracting increasing interest within the artificial intelligence medical fi...