Github copilot 指令

This study aimed to develop an accessible tool, derived using machine learning, to predict hypoglycaemia risk at the start of exercise and to provide clear, rapid risk assessment to support safer participation in exercise.

The Genomic Data Commons (GDC) provides access to high quality, harmonized cancer genomics data through a unified curation and analysis platform centered around patient cohorts. While GDC users can interactively create complex cohorts through the graphical Cohort Builder, users (especially new ones) may struggle to find specific cohort descriptors across hundreds of possible fields and properties. However, users may be better able to describe their desired cohort in free-text natural language.

Medical education increasingly incorporates digital technologies; however, many tools remain passive and text-based.

Case study asks Copilot users about its impact on their productivity, and seeks to find their perceptions mirrored in user data.

Exfoliative glaucoma (XFG) is characterized by elevated intraocular pressure (IOP) caused by fibrous deposits obstructing aqueous humor drainage, traditionally emphasizing mechanical factors. In this study, we aim to investigate the relationships between clinical parameters and autoimmune activity in exfoliative glaucoma (XFG) patients, and identify patterns of autoantibody reactivity among patient subgroups with differing levels of overall autoimmune activity.

The use of artificial intelligence-driven code completion tools, particularly the integration of GitHub Copilot with Visual Studio, has potential implications for Health Informatics education, particularly for students learning SQL and Python.