Special Issue: Artificial Intelligence and Machine Learning in Pediatrics

Kuru, Kaya orcid iconORCID: 0000-0002-4279-4166, De Goede, Christian, Caswell, Noreen orcid iconORCID: 0000-0001-6832-6822, R Hart, Gregory, Quon, Jennifer and Ehwerhemuepha, Louis (2023) Special Issue: Artificial Intelligence and Machine Learning in Pediatrics. Frontiers Media, Frontiers in Artificial Intelligence.

Full text not available from this repository.

Official URL: https://www.frontiersin.org/research-topics/48504/...


Over the past few decades, large volumes of healthcare data in different formats with multiple dimensions and complexities (i.e., the 10 Vs of Big Data), beyond the comprehension of human capacity have been created exponentially. New intelligent tools and methods are required to exploit these data volumes, particularly obtained using advanced sensor technologies (e.g., biosensors, medical imaging, laboratory tests, and genetic tests). Data analytic tools - Artificial Intelligence & Machine Learning (AI/ML) techniques - in the healthcare discipline are evolving rapidly to harvest these explosive increasing healthcare data volumes by uncovering complex nonlinear relationships and patterns given the particular datasets leading to thorough and up-to-date insights in a timely manner for early diagnosis of diseases, better treatment, effective decision-making, reducing healthcare costs, and making our lives safer, better and simpler in every aspect.

Within this context, the objective of this themed article collection aims to cover the following subjects particularly focusing on the pediatrics discipline.
• Big data analytics in pediatrics,
• Disease databases in pediatrics (e.g., rare diseases, disorders),
• Intelligent applications using the pediatrics disease databases,
• Intelligent methods processing every type of pediatric data,
• Datamining in pediatrics,
• Precision medicine/Personalized medicine in pediatrics using AI/ML,
• Diagnostics in pediatrics using AI/ML,
• Prognosis in pediatrics using AI/ML,
• Deep learning (DL) and Reinforcement Learning (RL) in pediatrics,
• Development of new treatment methods in pediatrics using AI/ML,
• Reduction of medical errors in pediatrics using AI/ML,
• Intelligent machines in pediatrics,
• Telemedicine in pediatrics using AI/ML,
• Discovery of new drugs in pediatrics using AI/ML,
• Use of cloud computing to process pediatric data,
• Ethics and regulatory framework of using AI/ML in pediatrics,
• Review papers discussing the use of AI/ML in pediatrics.

In this Research Topic, we are looking for original articles, opinion pieces, and reviews that focus on the above subjects. Manuscripts that are purely methodological, statistical, or conceptual are not eligible. Manuscripts should be accessible to a broad readership of clinicians and avoid a too-technical writing style for our audience.

Repository Staff Only: item control page