Artificial intelligence and biosensors: Transforming cancer diagnostics

Cancer is one of the leading causes of death worldwide. Early detection of cancer can play a decisive role in cancer treatment and improving survival rates. Conventional cancer detection methods, such as biopsy, imaging and blood tests are generally invasive and time-consuming, and their results have accuracy issues. Biosensors with artificial intelligence integration play a significant and evolving role in cancer diagnostics, offering non-invasive, rapid, and highly sensitive methods for early detection, monitoring, and treatment of cancer. Biosensors detect specific biomarkers associated with cancerous cells or tumours, such as nucleic acid (DNA, RNA), small molecules, peptides, proteins and metabolites. In recent years, many predictive artificial intelligence models and bioinformatics tools have been developed to integrate biosensors, emerging as powerful tools for cancer diagnostics. This review explores the role of biosensors in cancer detection, the development and application of predictive AI models and bioinformatics tools in cancer detection through biosensor technologies, and the challenges associated with their clinical adoption. • Early-stage cancer is a major challenge and needs an effective detection method to improve survival rates and treatment outcomes. • Conventional methods, such as biopsy, imaging, and blood tests, are invasive, time-consuming, and often lack accuracy, highlighting the need for more efficient alternatives. • Biosensors with artificial intelligence integration offer non-invasive, rapid, and highly sensitive methods for the early detection, monitoring, and treatment of cancer • Advanced bioinformatics tools and predictive AI models integration with biosensors need to improve for cancer diagnostics