Artificial intelligence in orthopedic research assistance: a resident's perspective

Area of Science:

• Orthopedic Research
• Medical Informatics
• Artificial Intelligence Applications

Background:

• Academic workflows in orthopedics face challenges in efficiency and data analysis.
• Evidence synthesis and literature reviews are time-consuming processes.
• Access to advanced analytical tools can be limited for researchers and residents.

Purpose of the Study:

• To review the transformative applications of artificial intelligence (AI) in orthopedic research.
• To explore how AI tools optimize academic workflows and evidence synthesis.
• To discuss the impact of AI on data analysis, researcher efficiency, and resident education.

Main Methods:

• Review of current AI technologies and platforms relevant to scientific research.
• Analysis of AI applications in literature review, data interpretation, and statistical analysis.
• Exploration of generative AI models (e.g., ChatGPT, GPT-4) and specialized platforms (e.g., Consensus, SciSpace).

Main Results:

• AI optimizes academic workflows, evidence synthesis, and access to data analysis.
• Generative AI and specialized platforms enhance literature reviews and document synthesis.
• AI facilitates interpretation of large datasets, saving time and increasing research efficiency.
• AI significantly impacts orthopedic resident education, promoting independence.

Conclusions:

• Artificial intelligence is a powerful tool revolutionizing orthopedic research and education.
• AI enhances efficiency, data interpretation, and accessibility of advanced analytics.
• Ethical considerations and challenges associated with AI in research require careful examination.