فهرست نشریات علمی دسترسی آزاد ایران

Artificial Intelligence (AI) is rapidly reshaping analytical chemistry by providing faster, more precise, and predictive approaches across various field of science. Utilizing machine learning, deep learning, and advanced computational methods, AI enables efficient management of complex datasets, automates analytical workflows, and enhances decision-making in pharmaceuticals, food safety, and clinical diagnostics. This review examines studies published up to 2025, highlighting key advancements, applications, and the integration of AI in analytical sciences. It emphasizes how AI-driven techniques such as spectroscopy, chromatography, proteomics, chemometrics, and bioinformatics, are transforming traditional experimental paradigms by enabling high-throughput analysis, predictive modeling, and real-time monitoring, thereby accelerating research and improving reproducibility. The review also addresses existing limitations, including dependence on large, high-quality datasets, limited interpretability of complex models, computational resource demands, and integration with existing laboratory infrastructure. Overcoming these limitations is essential to fully exploit AI’s potential for innovation, accuracy, and data-driven decision-making, ultimately advancing analytical chemistry and related scientific disciplines toward more intelligent, automated, and sustainable research practices.GRAPHICAL ABSTRACT