“…In particular, this is true because analysis processing via deep learning algorithms is quickly advancing , and the development of user-friendly and freely accessible pipelines from droplet image analysis is robust. − Making droplet emulsion generation quick and simple, moreover, especially correlates with the current trend seen in the field of nucleic acid detection. The focus is shifting toward not only high-resolution single-cell analysis ,, but also rapid and easy to use diagnostic and monitoring tools. ,,,− Nevertheless, when addressing detection of extremely small molecules in complex matrices (e.g., neurotransmitters and electrolytes), options are restrictive due to current scientific technological limitations. Often such target detection currently still requires very specific labels and/or specific complex experimental setups with costly hardware. ,,, There is, however, no doubt that droplet emulsion methods provide prospective workflows and labeling options.…”