Latest AI and machine learning research in pediatrics for healthcare professionals.
BACKGROUND: Delirium is a frequent postoperative complication among patients who have undergone cardiac surgery and is associated with prolonged hospitalization, cognitive decline, and increased mortality. Early prediction of delirium is therefore critical for initiating timely interventions. OBJECTIVE: This study proposes the development and validation of a machine learning-based model to predict...
OBJECTIVES: To evaluate the usability, usefulness and impact of a novel point of care natural language processing (NLP) system, Medical information AI Data Extractor (MiADE), to assist structured diagnosis recording in electronic health records. METHODS: Mixed methods evaluation of the implementation of MiADE in a major National Health Service hospital, with surveys, interviews and observed outpat...
This study aims to synthesize the perceptions and expectations of long-term caregivers regarding the use of nursing robots to inform strategies for en...
Individual animal identification is crucial for dairy cattle management, regulatory compliance, and enhancing food security. Although computer vision ...
PURPOSE OF REVIEW: The literature review is pertinent because diagnosing pediatric tuberculosis (PdTB) remains quite challenging, especially in areas ...
In forests of the southwestern US, the seasonality - or phenology - of tree growth is affected by a combination of limiting temperatures and water ava...
Congenital heart disease (CHD) is a major cause of infant mortality and presents life-long challenges to individuals living with these conditions. Gen...
Large language models (LLMs) are increasingly used by patients and families to interpret complex medical documentation, yet most evaluations focus onl...
OBJECTIVES: To examine the emotional, cognitive and dispositional experience of children and adolescents undergoing Lokomat rehabilitation by integrat...
BACKGROUND: Acute Kidney Injury (AKI) is common in neonates admitted to the Neonatal Intensive Care Unit (NICU). Neonatal AKI is associated with multi...
OBJECTIVE: The benefit of interventions to improve neonatal outcomes of preterm birth (PTB) must be balanced with the associated fetal and maternal ri...
OBJECTIVE: To describe the current use, limitations, and future directions of lesion network mapping in pediatric epilepsy. METHODS: Narrative review ...
Valvular heart disease (VHD) remains significantly underdiagnosed and undertreated. This review examines an artificial intelligence (AI)-enhanced 'spo...
OBJECTIVES: Celiac disease (CeD) is a common autoimmune condition requiring lifelong adherence to a gluten-free diet (GFD). Patients and caregivers in...
OBJECTIVES: This study explored the use of different applied machine learning (ML) classification algorithms to predict hospital admission for infants...
BACKGROUND: The use of artificial intelligence (AI) in medicine is rapidly evolving. However, its role in plastic and reconstructive surgery remains u...
BACKGROUND: Synthetic positron emission tomography (PET) imaging, enabled by deep learning, represents a promising approach to minimize radiation expo...
This study explores clinician leaders understanding and perception at site level towards machine learning (ML) decision support tools for paediatric r...