There are multiple skin diseases. Skin diseases manifest through lesions. Lesions can be discolorations, rashes, or bumps. The most common ones are Smallpox, Monkeypox, Measles, Lupus, Malignant Melanomas, among others. On the other hand, the healthcare system in Mexico is structured into three levels. The first level consists of small clinics, mostly rural. These clinics have a doctor and a nurse. They only provide general consultations and vaccines. Second-level clinics offer medical assistance up to hospitalization and childbirth surgeries. Finally, third-level clinics have all specialties. A patient is evaluated at level 1 and can be referred to a level 2 or 3 clinic. This work is focused on patients who can reach a level 1 or 2 clinic. The doctor must evaluate it, but is not a dermatologist or oncologist. Therefore, we propose a mobile device called D.A.N.N (Dermatologic Analysis with Neural Networks) that aims to take a photograph of the patient’s skin and identify the disease. This is considered a pre-diagnosis. Thus, it helps the doctor decide which specialty to refer to. This device can identify up to 5 diseases. To achieve this purpose, the device was assembled with a Raspberry Pi 4 and other attachments. For its operation, a trained Visual Transformer (ViT) model is incorporated. During training, a 99% accuracy was achieved, while during validation, a 91% accuracy was achieved. It is concluded that a mobile device can help doctors identify skin diseases and refer the patient to the corresponding specialist.