Artificial Intelligence in Public Health: Bridging Today’s Trends with Tomorrow’s Possibilities DOI Creative Commons
Daniele Giansanti, Giovanni Costantini

Bioengineering, Journal Year: 2025, Volume and Issue: 12(6), P. 559 - 559

Published: May 23, 2025

Driven by the unprecedented challenges of COVID-19 pandemic, healthcare sector has witnessed remarkable—and at times sometimes overwhelming—advancements in role artificial intelligence (AI) [...]

Language: Английский

Machine Learning in Pediatric Healthcare: Current Trends, Challenges, and Future Directions DOI Open Access
Hammad A. Ganatra

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(3), P. 807 - 807

Published: Jan. 26, 2025

Background/Objectives: Artificial intelligence (AI) and machine learning (ML) are transforming healthcare by enabling predictive, diagnostic, therapeutic advancements. Pediatric presents unique challenges, including limited data availability, developmental variability, ethical considerations. This narrative review explores the current trends, applications, future directions of ML in pediatric healthcare. Methods: A systematic search PubMed database was conducted using query: (“artificial intelligence” OR “machine learning”) AND (“pediatric” “paediatric”). Studies were reviewed to identify key themes, methodologies, challenges. Gaps research considerations also analyzed propose directions. Results: has demonstrated promise diagnostic support, prognostic modeling, planning for patients. Applications include early detection conditions like sepsis, improved imaging, personalized treatment strategies chronic such as epilepsy Crohn’s disease. However, challenges limitations, concerns, lack model generalizability remain significant barriers. Emerging techniques, federated explainable AI (XAI), offer potential solutions. Despite these advancements, gaps persist diversity, interpretability, frameworks. Conclusions: offers transformative addressing prognostic, While advancements highlight its promise, overcoming barriers trustworthiness is essential broader adoption. Future efforts should focus on enhancing developing standardized guidelines, improving transparency ensure equitable effective implementation care.

Language: Английский

Citations

1

Artificial Intelligence in Public Health: Bridging Today’s Trends with Tomorrow’s Possibilities DOI Creative Commons
Daniele Giansanti, Giovanni Costantini

Bioengineering, Journal Year: 2025, Volume and Issue: 12(6), P. 559 - 559

Published: May 23, 2025

Driven by the unprecedented challenges of COVID-19 pandemic, healthcare sector has witnessed remarkable—and at times sometimes overwhelming—advancements in role artificial intelligence (AI) [...]

Language: Английский

Citations

0