How can medical microrobots improve our awareness regarding the diagnosis and treatment of diseases?

Previous field and lab experience as a diagnostics scientist shows that effective diagnostic techniques relying hugely on consistent-based procedures which might be beyond human atenable capacity. 
However, nanotech and machine-driven operations that run on pre-programmed and micro-chipped indicators and detectors would be more reliable and effective. 

Based on my work on OmicsFusionNet, an AI-driven cancer diagnostic framework built on Illumina sequencing data, I see medical microrobots as supportive tools rather than replacements for sequencing technologies. Although microrobots are not capable of generating sequencing data themselves, they offer significant value as in vivo sampling and microenvironment-sensing systems. By enabling more precise and biologically representative sample collection, they can improve the quality of material used for downstream omics analyses. When such enriched data are integrated into AI-based platforms like OmicsFusionNet, they have the potential to strengthen early cancer detection, increase diagnostic accuracy, and support more personalized treatment decisions.

Owing to there minute size, they are very much important in the diagnosis of disease by identifying mild structural changes (microscopic lesions) and presence of microbs in the affected tissue. Moreover they can aid in detecting drug delivery and detecting the possible improvement of the affected tissue following chemotherapy or surgery.