Artificial intelligence-driven transformations in diabetes care: a comprehensive literature review.
Muhammad IftikharMuhammad SaqibSardar Noman QayyumRehana AsmatHassan MumtazMuhammad RehanIrfan UllahIftikhar Ud-DinSamim NooriMaleeka KhanEhtisham RehmanZain EjazPublished in: Annals of medicine and surgery (2012) (2024)
Artificial intelligence (AI) has been applied in healthcare for diagnosis, treatments, disease management, and for studying underlying mechanisms and disease complications in diseases like diabetes and metabolic disorders. This review is a comprehensive overview of various applications of AI in the healthcare system for managing diabetes. A literature search was conducted on PubMed to locate studies integrating AI in the diagnosis, treatment, management and prevention of diabetes. As diabetes is now considered a pandemic now so employing AI and machine learning approaches can be applied to limit diabetes in areas with higher prevalence. Machine learning algorithms can visualize big datasets, and make predictions. AI-powered mobile apps and the closed-loop system automated glucose monitoring and insulin delivery can lower the burden on insulin. AI can help identify disease markers and potential risk factors as well. While promising, AI's integration in the medical field is still challenging due to privacy, data security, bias, and transparency. Overall, AI's potential can be harnessed for better patient outcomes through personalized treatment.
Keyphrases
- artificial intelligence
- machine learning
- big data
- type diabetes
- glycemic control
- deep learning
- risk factors
- cardiovascular disease
- healthcare
- systematic review
- sars cov
- human health
- public health
- risk assessment
- insulin resistance
- coronavirus disease
- adipose tissue
- high throughput
- skeletal muscle
- single cell
- combination therapy
- social media