Latest AI and machine learning research in pediatrics for healthcare professionals.
Foundation models, first introduced in 2021, are large-scale pre-trained models (e.g., large language models (LLMs) and vision-language models (VLMs)) that learn from extensive unlabeled datasets through unsupervised methods, enabling them to excel in diverse downstream tasks. These models, like GPT, can be adapted to various applications such as question answering and visual understanding, outp...
With the rapid growth of multi-modal data from social media, short video platforms, and e-commerce, content-based retrieval has become essential for efficiently searching and utilizing heterogeneous information. Over time, retrieval techniques have evolved from Unimodal Retrieval (UR) to Cross-modal Retrieval (CR) and, more recently, to Composed Multi-modal Retrieval (CMR). CMR enables users to ...
BACKGROUND AND AIMS: Robust and convenient risk stratification of patients with paediatric and adult congenital heart disease (CHD) is lacking. This s...
BACKGROUND: Multianalyte machine learning (ML) models can potentially identify previously undetectable wrong blood in tube (WBIT) errors, improving up...
Large language models (LLMs) hold substantial promise for clinical decision support. However, their widespread adoption in medicine, particularly in...
BACKGROUND: Chronic rejection forms the leading cause of late graft loss in pediatric kidney transplant recipients. Despite improvement in short-term ...
Intelligent traditional Chinese medicine (TCM) is a key pathway toward the modernization and globalization of TCM in the era of artificial intelligenc...
BACKGROUND: International Classification of Disease (ICD) codes can accurately identify patients with certain congenital heart defects (CHDs). In ICD-...
OBJECTIVE: To evaluate the accuracy and comprehensiveness of eight free, publicly available large language model (LLM) chatbots in addressing common q...
Pain is a complex, multidimensional experience involving significant challenges in both diagnosis and management. While acute pain serves as a critica...
The test-negative design (TND), which is routinely used for monitoring seasonal flu vaccine effectiveness (VE), has recently become integral to COVID-...
Despite advances in methods to interrogate tumor biology, the observational and population-based approach of classical cancer research and clinical ...
The effectiveness of zero-shot classification in large vision-language models (VLMs), such as Contrastive Language-Image Pre-training (CLIP), depend...
Predicting seizure freedom is essential for tailoring epilepsy treatment. But accurate prediction remains challenging with traditional methods, espe...
Foundation models are becoming increasingly effective in the medical domain, offering pre-trained models on large datasets that can be readily adapt...
Birth weight serves as a fundamental indicator of neonatal health, closely linked to both early medical interventions and long-term developmental ri...
Cerebral Palsy (CP) is a prevalent motor disability in children, for which early detection can significantly improve treatment outcomes. While skele...
Mentoring software is a pivotal innovation in addressing critical challenges in teacher development within educational institutions. This study expl...
Social media enables dynamic user engagement with trending topics, and recent research has explored the potential of large language models (LLMs) fo...
Weed management remains a critical challenge in agriculture, where weeds compete with crops for essential resources, leading to significant yield lo...