## 3 Materials and Methods
### MEX-IEM Dataset  
For experimental purposes, the MEX-IEM dataset was developed at UMAE No. 1 Bajio Public Hospital, part of the Mexican Social Security Institute (denoted as the IMSS, its acronym in Spanish), located in Guanajuato, Mexico. The MEX-IEM dataset comprises 4760 IEM images from 340 women with an age range of 25 to 70 years, annotated by physicians in terms of their corresponding BI-RADS level. Anthropometric and clinical data, such as data on pregnancy, lactation, antecedents of hormonal or surgical treatments, and the electrical conductivity of the breast glands, as well as the risk factors associated with breast cancer, were collected. The data collection followed the ethical norms established by  
\begin{table}
\begin{tabular}{l l l} \hline \hline
**BI-RADS** & **EIM Interpretation** & **EIM Scale** \\ \hline
0 & Insufficient sample & No score \\
1 & Undefined lesion & 0–1 \\
2 & Benign tumors—routine mammography & 2–3 \\
3 & Probably benign & 4 \\
4 & Suspicious anomaly—biopsy recommended & 5–7 \\
5 & High suspicion of malignancy—biopsy and treatment & 8–10 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Correspondence between BI-RADS and EIM scales.  
the IMSS National Commission for Scientific Research and was approved by its Research Ethics Committee under the protocol number R-2017-785-108. All the participants were informed about the procedures and provided their written consent to participate voluntarily in the study. Table 2 presents a summary of the features of the MEX-IEM dataset as well as the inclusion and exclusion criteria used during recruitment.  
Figure 1 illustrates the appearance of breast cross-sections from an EIM package and their corresponding depth, allowing for the analysis of the variation in the conductivity distribution at different tissue levels. The separation between the first and second slices is 4 mm and increases to 7 mm for subsequent levels, optimizing the visibility and allowing for the detailed analysis of breast structures across the different slices. In the color maps, a high conductivity index (red) is associated with high-density breast tissue, while lower conductivity values (blue) are observed in areas with a predominance of fatty tissue [32]. For example, the nipple in the first layer (reference region) presents a high conductivity index since it is composed of more fibrous and dense tissue compared to adipose tissue. However, in deeper layers, this composition shifts towards a predominance of fatty tissue, resulting in a decrease in the conductivity index value.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Feature** & **Description** \\ \hline Number of patients & 340 (BR1 = 85, BR2 = 85, BR3 = 128, BR4 = 38, BR5 = 4) \\ EIM package & 7 images per breast \\ Number of images & 4760 (288 \(\times\) 288 pixels) \\ Age range & 25 to 70 years old \\ Study design & Clinical, epidemiological, observational, prospective, cross-sectional, and serial screening study \\ Device used & MEIK v5.6 (SIM-technika, Russia, Yaroslavl) \\ Exploration depths & From the surface to the inner layers of the breast tissue \\ Physiological conditions considered & Pregnancy, breastfeeding, recent hormonal or surgical treatments, breast prostheses due to mastectomy or cosmetic surgery, etc. \\ Risk factors & Age of patient, body mass index, parity, age at menarche, age at menopause, hormonal therapy, family history of breast cancer, alcohol consumption, and smoking \\ \hline \hline \end{tabular}
\end{table}
Table 2: Description summary of MEX-IEM-DB database.  
Figure 1: Images of the seven layers in an EIM package representing the breast tissue information at different depths, from the most superficial (Layer 1) to the deepest (Layer 7). The color bar is associated with the conductivity index (IC) scale.