In recent years, the rapid advancement of artificial intelligence technology has led to its increasingly widespread application in basic medical data analysis. Artificial intelligence has undergone a swift evolution from expert rule⁃based systems to data⁃driven deep learning and multi⁃modal models, bringing groundbreaking progress to research fields such as genomics, protein structure prediction, single⁃cell transcriptomics, biological sequence analysis, and microbiology. However, these technologies also face bottlenecks, including data privacy concerns, resource limitations, and insufficient interpretability. This paper primarily explores the current applications and key methodologies of artificial intelligence in basic medical data analysis, along with the challenges and future development trends.  

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