Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence in the Management of Obesity
1
Zitationen
1
Autoren
2025
Jahr
Abstract
The prevalence of obesity has increased significantly in the last few years. Addressing obesity needs multifaceted strategy including prevention, accurate diagnosis, treatment of secondary causes, diet and exercise, behavioral changes and long term management. In addition it involves integration of multiple teams including endocrinologist, respiratory medicine, ENT, psychiatry, physiotherapy, diet, and bariatric surgeon. Artificial intelligence can help with each of these aspects by enabling predictive analysis, behavioral intervention in real time and improving patient outcome. There are certain challenges in integrating AI with patient management including ensuring data privacy and mitigating algorithm bias. But overall, it represents a promising tool to empower both the individual and the physician treating obesity.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.400 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.261 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.695 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.506 Zit.