: Artificial Intelligence techniques are widely used for medical purposes nowadays. One of the crucial applications is cancer detection. Due to the sensitivity of such applications, medical workers and patients interacting with the system must get a reliable, transparent, and explainable output. Therefore, this paper examines the interpretability and explainability of the Logistic Regression Model (LRM) for breast cancer detection. We analyze the accuracy and transparency of the LRM model. Additionally, we propose an NLP-based interface with a model interpretability summary and a contrastive explanation for users. Together with textual explanations, we provide a visual aid for medical practitioners to understand the decision-making process better.

Introduction/Objective. The purpose of this study was to assess the effectiveness of different approaches in the treatment of metastatic melanoma in daily clinical practice in a situation with limited and late availability of new drugs in a resource-limited country and to compare these parameters with those reported in clinical studies and from other real-world data. Methods. Main methods included assessment of overall survival (OS) and progression-free survival (PFS). Patients were included in the study if they were treated with first or second-line systemic therapy for radiologically/pathologically confirmed metastatic melanoma. Patients were divided into four groups based on the type of therapy they received: chemotherapy (dacarbazin), BRAF inhibitor (vemurafenib), BRAF/MEK inhibitors (vemurafenib/cobimetinib and trametinib/dabrafenib) and anti PD-1 therapy with pembrolizumab. Results. Regardless of the line of therapy, the calculated median OS in chemotherapy and vemurafenib group was nine months. The median OS in the BRAF/MEK inhibitor group was 14 months and 15 months in the pembrolizumab group. Median PFS in the chemotherapy group was four months, seven months for vemurafenib, in the BRAF/MEK inhibitor group nine months and in the pembrolizumab group six months. There was a statistically significant difference in survival between first and second-line therapy in the pembrolizumab group. Conclusion. Our results showed lower median OS and PFS in comparison to reported data from clinical trials. Compared to other real-world data from countries with similar problems related to the late reimbursement of new drugs, our research has shown similar results.