Latest AI and machine learning research in pediatrics for healthcare professionals.
BACKGROUND: Ensuring antibiotics are prescribed only when necessary is crucial for maintaining their effectiveness and is a key focus of public health initiatives worldwide. In cases of sinusitis, among the most common reasons for antibiotic prescriptions in children, healthcare providers must distinguish between bacterial and viral causes based on clinical signs and symptoms. However, due to the ...
Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infection who have ≥2 in the Phoenix Sepsis Score. The adoption of the Phoenix sepsis criteria eliminated the Systemic Inflammatory Response Syndrome criteria from the definition of pediatric sepsis. The objective of this study is to derive and validate machine learning models predicting in-hospital mortal...
BACKGROUND: Perimembranous ventricular septal defect (PMVSD) is a prevalent congenital heart disease, presenting challenges in predicting spontaneous ...
BACKGROUND: Medical images play an important role in diagnosis and treatment of pediatric solid tumors. The field of radiology, pathology, and other i...
Machine learning (ML) holds great promise in advancing risk prediction and stratification for neuroblastoma, a highly heterogeneous pediatric cancer. ...
The Yellow River Economic Belt, where the degree of digital economy development is uneven, is the first research object used in this study. It then su...
BACKGROUND: An increasing number of individuals use online Artificial Intelligence (AI) - based chatbots to retrieve information on health-related top...
Computer-aided diagnosis (CAD) systems have greatly improved the interpretation of medical images by radiologists and surgeons. However, current CAD...
Although social bots can be engineered for constructive applications, their potential for misuse in manipulative schemes and malware distribution ca...
The COVID-19 vaccine development, manufacturing, transportation, and administration proved an extreme logistics operation of global magnitude. Globa...
Introduction: Healthcare AI models often inherit biases from their training data. While efforts have primarily targeted bias in structured data, men...
Hirschsprung's disease (HD) is a congenital birth defect diagnosed by identifying the lack of ganglion cells within the colon's muscularis propria, ...
Sentiment analysis of textual content has become a well-established solution for analyzing social media data. However, with the rise of images and v...
Model immunization is an emerging direction that aims to mitigate the potential risk of misuse associated with open-sourced models and advancing ada...
Monitoring growth behavior of maize plants such as the development of ears can give key insights into the plant's health and development. Traditiona...
Referring multi-object tracking (RMOT) is an emerging cross-modal task that aims to localize an arbitrary number of targets based on a language expr...
Pediatric Emergency Department (PED) overcrowding presents a significant global challenge, prompting the need for efficient solutions. This paper in...
The measurement of fetal thalamus diameter (FTD) and fetal head circumference (FHC) are crucial in identifying abnormal fetal thalamus development a...
Artificial Intelligence (AI) is a broad field that is upturning mental health care in many ways, from addressing anxiety, depression, and stress to ...
As society rapidly digitizes, successful aging necessitates using technology for health and social care and social engagement. Technologies aimed to s...