Latest AI and machine learning research in domestic violence for healthcare professionals.
Depression is a global health concern with a critical need for increased patient screening. Speech technology offers advantages for remote screening but must perform robustly across patients. We have described two deep learning models developed for this purpose. One model is based on acoustics; the other is based on natural language processing. Both models employ transfer learning. Data from a d...
When it comes to classifying child sexual abuse images, managing similar inter-class correlations and diverse intra-class correlations poses a significant challenge. Vision transformer models, unlike conventional deep convolutional network models, leverage a self-attention mechanism to capture global interactions among contextual local elements. This allows them to navigate through image patches...
Talking face generation (TFG) allows for producing lifelike talking videos of any character using only facial images and accompanying text. Abuse of...
The generation of high-quality medical time series data is essential for advancing healthcare diagnostics and safeguarding patient privacy. Specific...
Systematic reviews (SRs) are essential for evidence-based guidelines but are often limited by the time-consuming nature of literature screening. We ...
The reproducibility of computational pipelines is an expectation in biomedical science, particularly in critical domains like human health. In this ...
Score-based Generative Models (SGMs) have demonstrated remarkable generalization abilities, e.g. generating unseen, but natural data. However, the g...
We propose a pipeline for gaining insights into complex diseases by training LLMs on challenging social media text data classification tasks, obtain...
Predictive machine learning (ML) models are computational innovations that can enhance medical decision-making, including aiding in determining opti...
As command-line interfaces remain integral to high-performance computing environments, the risk of exploitation through stealthy and complex command...
Numerous politicians use social media platforms, particularly X, to engage with their constituents. This interaction allows constituents to pose que...
In medical reporting, the accuracy of radiological reports, whether generated by humans or machine learning algorithms, is critical. We tackle a new...
With the emergence of large-scale vision-language models, realistic radiology reports may be generated using only medical images as input guided by ...
Sudden Cardiac Arrest (SCA) is the leading cause of death among athletes of all age levels worldwide. Current prescreening methods for cardiac risk ...
Loneliness, or the lack of fulfilling relationships, significantly impacts a person's mental and physical well-being and is prevalent worldwide. Pre...
Deep learning models are widely used to process Computed Tomography (CT) data in the automated screening of pulmonary diseases, significantly reduci...
Together with industry experts, we are exploring the potential of head-mounted augmented reality to facilitate safety inspections on high-rise const...
The field of traumatic hemostasis is currently confronted with numerous challenges, particularly in addressing the treatment of non-compressible torso...
Virtual screening of small molecules against protein targets can accelerate drug discovery and development by predicting drug-target interactions (D...
Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat ...