**Appendix A**

As we have written in the introduction section, to the best of our knowledge, to date, there are no public or private laboratories that carry out the examination of the cell population of the nasal mucosa routinely, as instead it is done for hematological tests. The first studies about the automatic extraction and classification of the cells of the nasal mucosa were published by some of the authors of this paper. Now, specialists would prefer to carry out the entire evaluation of the cell population on a personal device, such as a smartphone, fully automatically, with the aim of increasing the screening and routine monitoring of nasal disease through cytology.

The use of a smartphone-based system also guarantees the preservation of the privacy and security of patient information. On the other hand, it makes it possible to send patient data and images to the Electronic Medical Record [8] to follow-up with the patient or to obtain a "second opinion", an increasingly widespread practice. However, this further possibility is reserved for patients who request it and, for these, a security protocol should be used. When the classification is carried out completely on the smartphone, nothing must be transferred remotely; however, several problems have to be overcome first, among all the limitations of the computational capacity of mobile architectures.

Our system is based on well-known algorithms in the literature—not state-of-the-art, but effective enough for our purpose. These are already sustainable from a computational point of view from medium–low end architectures, such as the Xiaomi, used for this experimentation. The use of traditional image processing techniques to preprocess the image is also battery-efficiently on a mobile phone.

At this stage, the system designed and described in this paper is limited to the extraction of cells from the microscopic field. Once this is done, the specialist can decide to manually evaluate the segmented cells or to send them to the Rhino-cyt platform for a fast classification. So, the system is already very useful.
