Artificial intelligence perspective in the future of endocrine diseases.
Mandana HasanzadHamid Reza Aghaei MeybodiNegar SarhangiBagher LarijaniPublished in: Journal of diabetes and metabolic disorders (2022)
In recent years, artificial intelligence (AI) shows promising results in the diagnosis, prediction, and management of diseases. The move from handwritten medical notes to electronic health records and a huge number of digital data commenced in the era of big data in medicine. AI can improve physician performance and help better clinical decision making which is called augmented intelligence. The methods applied in the research of AI and endocrinology include machine learning, artificial neural networks, and natural language processing. Current research in AI technology is making major efforts to improve decision support systems for patient use. One of the best-known applications of AI in endocrinology was seen in diabetes management, which includes prediction, diagnosis of diabetes complications (measuring microalbuminuria, retinopathy), and glycemic control. AI-related technologies are being found to assist in the diagnosis of other endocrine diseases such as thyroid cancer and osteoporosis. This review attempts to provide insight for the development of prospective for AI with a focus on endocrinology.
Keyphrases
- artificial intelligence
- big data
- machine learning
- glycemic control
- type diabetes
- deep learning
- electronic health record
- cardiovascular disease
- neural network
- emergency department
- blood glucose
- decision making
- autism spectrum disorder
- primary care
- weight loss
- postmenopausal women
- bone mineral density
- current status
- adipose tissue
- risk factors
- body composition
- skeletal muscle