OBJECTIVE: To quantitatively assess the performance of ChatGPTv4, an Artificial Intelligence Language Model, in adhering to clinical guidelines for Diminished Ovarian Reserve (DOR) over two months, evaluating the model's consistency in providing guid...
With the rapid development of computer science, there is an increasing demand for the use of causal inference methods and machine learning in the research of endocrine disorders and their long-term health outcomes. However, studies on the effective a...
Journal of endocrinological investigation
Nov 16, 2023
BACKGROUND AND AIM: Artificial intelligence (AI) has emerged as a promising technology in the field of endocrinology, offering significant potential to revolutionize the diagnosis, treatment, and management of endocrine disorders. This comprehensive ...
Journal of pediatric endocrinology & metabolism : JPEM
Aug 18, 2023
Artificial Intelligence (AI) is integrating itself throughout the medical community. AI's ability to analyze complex patterns and interpret large amounts of data will have considerable impact on all areas of medicine, including pediatric endocrinolog...
OBJECTIVE: To determine whether graph neural network based models of electronic health records can predict specialty consultation care needs for endocrinology and hematology more accurately than the standard of care checklists and other conventional ...
The Journal of clinical endocrinology and metabolism
May 17, 2024
Artificial intelligence (AI) holds the promise of addressing many of the numerous challenges healthcare faces, which include a growing burden of illness, an increase in chronic health conditions and disabilities due to aging and epidemiological chang...
The Journal of clinical endocrinology and metabolism
May 17, 2024
In endocrinology, the types and quantity of digital data are increasing rapidly. Computing capabilities are also developing at an incredible rate, as illustrated by the recent expansion in the use of popular generative artificial intelligence (AI) ap...
This study investigated the diagnostic performance, feasibility, and end-user experiences of an artificial intelligence (AI)-assisted diabetic retinopathy (DR) screening model in real-world Australian healthcare settings. The study consisted of two c...