infection is a critical contributor to GC. The diagnostic confirmation of GC is generally obtained at late stages owing to the delayed onset of symptoms. Early detection can significantly improve the disease outcomes. Several approaches, like endoscopy, MRI, and computed tomography, are conventionally employed. But they often have certain drawbacks, such as less accessibility, invasiveness, and potential false results. Delayed diagnosis and poor prognosis by conventional strategies have underlined the need for an efficient and precise solution. These obstacles can be mitigated by implementing advanced biosensing platforms. The amalgamation of nanotechnology, machine learning, and advanced computational intelligence has extensively evolved sensor technology. This review offers a holistic overview of GC pathogenicity and conventional diagnostics with special emphasis on recently fabricated biosensors. Advanced biosensing platforms, like CRISPR-Cas, smartphone-integrated, breath-based, and ingestible biosensors, are also explored. This review further highlights the translational perspectives along with the increasing role of AI and advanced algorithms. With a critical discussion on key challenges, this article provides a future roadmap for the detection of GC biomarkers. Significant innovations are needed to translate biosensors into a state-of-the-art technique in GC diagnostics.
Yadav et al. (Sun,) studied this question.