AIMC Topic: Pediatrics

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Machine learning-based approaches for distinguishing viral and bacterial pneumonia in paediatrics: A scoping review.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Pneumonia is the leading cause of hospitalisation and mortality among children under five, particularly in low-resource settings. Accurate differentiation between viral and bacterial pneumonia is essential for guiding approp...

Artificial intelligence in pediatric otolaryngology: A state-of-the-art review of opportunities and pitfalls.

International journal of pediatric otorhinolaryngology
BACKGROUND: Artificial Intelligence (AI) and machine learning (ML) have transformative potential in enhancing diagnostics, treatment planning, and patient management. However, their application in pediatric otolaryngology remains limited as the uniqu...

Comparative Analysis of Information Quality in Pediatric Otorhinolaryngology: Clinicians, Residents, and Large Language Models.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Pediatric otorhinolaryngology (ORL) addresses complex conditions in children, requiring a tailored approach for patients and families. With artificial intelligence (AI) gaining traction in medical applications, this study evaluates the qua...

Digital Pathology and Artificial Intelligence in Pediatric Pathology.

Surgical pathology clinics
Applications of artificial intelligence (AI) and machine learning (ML) are rapidly developing to support the diagnosis and classification of pathology specimens. These tools rely on digitization of pathology glass slides as whole slide images, allowi...

Use of an Untrained Large Language Model for Antibiotic Prescription in Pediatric Infectious Diseases at Primary Care Settings: A Study From the Italian Society for Pediatric Infectious Diseases.

The Pediatric infectious disease journal
The development of artificial intelligence systems is revolutionizing many fields of medicine, but specific studies are still missing in pediatrics. In our study, we showed that an untrained free-to-use large language model provided reliable response...

The potential of artificial intelligence to transform medicine.

Current opinion in pediatrics
PURPOSE OF REVIEW: Increased incorporation of artificial intelligence in medicine has raised questions regarding how it can enhance efficiency in concert with providing accurate medical information without violating patient privacy. Pediatricians sho...

Comparative analysis of GPT-4 and Google Gemini's consistency with pediatric otolaryngology guidelines.

International journal of pediatric otorhinolaryngology
OBJECTIVE: To evaluate the accuracy and completeness of large language models (LLMs) in interpreting pediatric otolaryngology guidelines.

Artificial intelligence in clinical practice: a cross-sectional survey of paediatric surgery residents' perspectives.

BMJ health & care informatics
OBJECTIVES: The aim of this study was to compare the performances of residents and ChatGPT in answering validated questions and assess paediatric surgery residents' acceptance, perceptions and readiness to integrate artificial intelligence (AI) into ...

What makes a 'good' decision with artificial intelligence? A grounded theory study in paediatric care.

BMJ evidence-based medicine
OBJECTIVE: To develop a framework for good clinical decision-making using machine learning (ML) models for interventional, patient-level decisions.

Extracting Pediatric Information from Summaries of Product Characterics with a Large Language Model and No-Code.

Studies in health technology and informatics
Accurate medication information is important for children, as dosing errors can have severe consequences compared to adults. We propose an automated method to extract pediatric information from Summaries of Product Characteristics (SPC). We used AirO...