Artificial intelligence (AI) in medical imaging is rapidly growing to advance healthcare in adults but is less developed in the pediatric population. AI algorithms trained on adults often cannot be applied to children due to differences in body size, growth, disease types, disorder manifestations, imaging bioeffects and socioeconomic factors.

2024年8月12日 · There is a dearth of artificial intelligence (AI) development and research dedicated to pediatric radiology. The newest iterations of large language models (LLMs) like ChatGPT can process image and video input in addition to text. They are thus theoretically capable of providing impressions of input radiological images.

2024年11月18日 · We outline the unique challenges of applying AI in pediatric imaging, such as data scarcity and distinct clinical characteristics, and discuss the current uses of AI in pediatric radiology, including both image interpretive and non-interpretive tasks.

2021年5月27日 · This review focuses on the use of AI within pediatric radiology for image interpretation, with descriptive summaries of the literature to date. We highlight common features that enable successful application of the technology, along with some of the limitations that can inhibit the development of this field.

In this article, we discuss a variety of possible ‘use cases’ in paediatric radiology from a patient pathway perspective where AI has either been implemented or shown early-stage feasibility, while also taking inspiration from the adult literature to propose potential areas for future development.

2023年7月25日 · Only a few FDA-authorized image-based AI algorithms have been developed specifically for children or adequately validated on pediatric cohorts. As a result, there is a critical need for an appropriate framework for pediatric AI development, validation, implementation, and …

AI has shown promise in pediatric radiology, where machine learning algorithms can analyze medical images to detect conditions such as pneumonia, brain tumors, and congenital heart defects with high accuracy. 20 In precision oncology, AI can identify specific genetic mutations in pediatric cancers, allowing for the selection of targeted ...

2019年2月11日 · Here, we present an AI-based NLP model that can process free text from physicians’ notes in the EHR to accurately predict the primary diagnosis in a pediatric population.

2025年2月24日 · Dr Srinivasan Suresh presents a comprehensive overview of generative AI in health care, with a focus on potential applications in the care of children. Dr Karim Hanna describes and demonstrates AI-enhanced approaches to medical education.

We identified 55 articles that implemented an AI model to interpret pediatric chest radiographs or pediatric and adult chest radiographs. Classification of chest radiographs as pneumonia was the most common application of AI, evaluated in 65% of the studies.