Latest AI and machine learning research in pediatrics for healthcare professionals.
Pediatric sarcomas are rare and diverse, often leading to misclassification that hampers prognosis and treatment planning. We collected and harmonized histology images from multiple medical centers and developed accurate, generalizable classifiers for sarcoma subtype classification using deep learning techniques on digitized histology slides. A pediatric sarcoma histology dataset was amassed from ...
Artificial intelligence (AI) has impacted healthcare at urban and academic medical centers globally. The current focus on AI deployments in urban areas and the history of US urban-rural digital divides raises concerns that the promise of AI may not be realized in rural communities. This may exacerbate well-documented health disparities. Without the benefits of AI-driven improvements in patient out...
Acute kidney injury (AKI) is a serious and common complication among critically ill neonates. Preventing or treating AKI early requires timely predict...
This paper addresses the problem of detecting possible serious bacterial infection (pSBI) of infancy, i.e. a clinical presentation consistent with bac...
Bicuspid aortic valve (BAV) is the most common congenital heart defect but often evades timely diagnosis due to variable clinical presentations. Prior...
This study explores clinician understanding and perception at site lead level towards machine learning (ML) decision support tools for paediatric rela...
Large language models (LLMs) have gained traction in medicine, but there is limited research comparing closed- and open-source models in subspecialty ...
Brain MRI is the main imaging modality for pediatric brain tumors (PBTs); however, incomplete MRI exams are common in pediatric neuro-oncology setting...
There is great potential for artificial Intelligence (AI) and machine learning (ML) to support decision making in emergency departments (ED), however ...
Intensive care departments generate vast multivariate time series data capturing the dynamic physiological states of critically ill patients. Despite ...
The application of large language models (LLMs) in pediatric medicine requires rigorous performance evaluation prior to clinical implementation. To ev...
Chatbots have the potential to reduce barriers to pre-exposure prophylaxis (PrEP), including lack of awareness, misconceptions, and stigma, by providi...
Handwritten home-based vaccination records (HBRs) are a vital source of immunization data, yet manual transcription in household surveys is time-consu...
Artificial intelligence (AI) has potentially shown promise in interpreting ultrasound imaging through flexible pattern recognition and algorithmic lea...
Diagnosis coding is essential for clinical care, research validity, and hospital reimbursement. In neonatal settings, manual coding is frequently erro...
Motor neuron disease (MND) is a rapidly progressive and fatal neurodegenerative condition, making early diagnosis critical for optimizing patient outc...
Decision-making in perinatal management of extremely preterm infants is challenging. Mortality prediction tools may support decision-making. We used p...
The early detection of adverse drug events (ADEs) became a critical issue in clinical research after the thalidomide disaster in 1961, which resulted ...
Iron overload promotes atherosclerosis in mice and causes vascular dysfunction in humans with Hemochromatosis. However, data are controversial on whet...
Low back pain (LBP) is common among adolescent cricketers, often due to repetitive lumbar stress. This study investigated LBP among 450 adolescent cri...