Latest AI and machine learning research in parenting for healthcare professionals.
Medical ultrasound (US) image segmentation and quantification can be challenging due to signal dropouts, missing boundaries, and presence of speckle, which gives images of similar objects quite different appearance. Typically, purely intensity-based methods do not lead to a good segmentation of the structures of interest. Prior work has shown that local phase and feature asymmetry, derived from th...
BACKGROUND: Huge amounts of electronic biomedical documents, such as molecular biology reports or genomic papers are generated daily. Nowadays, these documents are mainly available in the form of unstructured free texts, which require heavy processing for their registration into organized databases. This organization is instrumental for information retrieval, enabling to answer the advanced querie...
Labral hypertrophy is a distinct feature in hip dysplasia. Occasionally, very small, hypotrophic labra are observed. However, there is no literature c...
Octopus suckers are able to attach to all nonporous surfaces and generate a very strong attachment force. The well-known attachment features of this a...
The use of robots in therapy for children with autism spectrum disorder (ASD) raises issues concerning the ethical and social acceptability of this te...
Animals have demonstrated the ability to move through, across and over some of the most daunting environments on earth. This versatility and adaptabil...
Prognostics is a core process of prognostics and health management (PHM) discipline, that estimates the remaining useful life (RUL) of a degrading mac...
Diabetes mellitus is a chronic disease and a worldwide public health challenge. It has been shown that 50-80% proportion of T2DM is undiagnosed. In th...
We introduce AraMS-28k, the largest publicly released line-level dataset of genuine historical Arabic manuscripts, comprising 14 books, 3,043 pages, a...
Neural network training has an oracle problem: a run can converge normally and yield a usable model while the software beneath it computes something o...
Background. Phthalates are hypothesised to act as metabolic disruptors, and machine learning applied to the National Health and Nutrition Examination ...
Objective To develop and evaluate an automated large language model (LLM)-based framework for conducting meta-analyses of nutrition-related exposures ...
Decellularized extracellular matrix (dECM) scaffolds are increasingly used in regenerative medicine, yet the extent to which processed placental dECM ...
Background: The growing burden of lifestyle-related chronic diseases has increased the need for clinically interpretable decision-support tools capabl...
Human milk contains a diverse array of metabolites that contribute to infant nutrition, immune development, and microbial colonization. The maternal f...
The aim of this paper is to (1) identify textual and visual themes and sub-themes associated with the #wellbeing hashtag on Instagram, (2) assess thei...
Food image segmentation plays a vital role in health-related applications such as nutrition tracking and personalized health monitoring. However, exis...
AI researchers describe state-of-the-art models as one thing repeated at scale: the Transformer, wired identically for text, pixels, or speech. Neuros...
Abstract Background Despite a rising global psychiatric burden, a treatment gap persists where the majority of symptomatic individuals remain unmedica...
Multimodal Large Language Models (MLLMs) are increasingly used for dietary assessment from meal images, where retrieval-augmented grounding was shown ...