## 3 Methods
### Dataset Diversity  
A well-defined evaluation dataset is essential for ensuring unbiased and generalizable results. This section addresses potential concerns regarding dataset diversity by detailing the representativeness of the test data, including variations in patient demographics and disease types, while also providing a comprehensive description of the data sources.  
The COVID-19 dataset [18] is derived from the volumes folder ([[https://academicrrents.com/details/136](https://academicrrents.com/details/136) ffddd0959108 becb2b3a86630 bec049 fc0 ff]([https://academicrrents.com/details/136](https://academicrrents.com/details/136) ffddd0959108 becb2b3a86630 bec049 fc0 ff), accessed on 6 March 2025) within the COVID-19 image dataset collection [22]. Its primary contribution lies in providing high-quality labels for objects of interest created by experienced radiologists. The data sources are detailed in [22] and include reputable platforms such as Radiopaedia ([[https://radiopaedia.org/](https://radiopaedia.org/)]([https://radiopaedia.org/](https://radiopaedia.org/)), accessed on 6 March 2025) and Coronacases ([[https://coronacases.org/](https://coronacases.org/)]([https://coronacases.org/](https://coronacases.org/)), accessed on 6 March 2025). As its name suggests, the dataset specifically includes COVID-19 cases.  
The Montgomery dataset [20] was collected in collaboration with the Department of Health and Human Services, Montgomery County, MD, USA. In addition to medical images, the dataset authors provide manually segmented lung masks. These segmentations were performed under the supervision of a radiologist, following anatomical landmarks. The dataset includes tuberculosis cases from a screening program conducted in Montgomery County.  
Although both datasets are anonymized to protect patient privacy, their curators have provided certain demographic information. Figure 2 shows the sex and age distribution for these datasets.  
Figure 2: Sex and age distribution in COVID-19 and Montgomery datasets.  
The sex distribution in the COVID-19 and Montgomery datasets is not perfectly balanced but remains relatively close to an even split, according to the data provided in their respective publications. Specifically, the COVID-19 dataset consists of 61.90% male and 38.10% female cases, while the Montgomery dataset includes 45.99% male and 54.01% female cases.  
The age distribution in the COVID-19 dataset is skewed toward middle-aged and older individuals, with samples between 25 and 80 years old and prominent peaks around 40, 50, and 70 years old. This suggests a focus on conditions prevalent in middle-aged and elderly populations. In contrast, the Montgomery dataset exhibits a broader and more evenly distributed age range, spanning from young (10s and 20s) to elderly individuals (80s and 90s). The distribution shows noticeable peaks around 30 and 55 years old, indicating a more balanced representation across different age groups. While the COVID-19 dataset is particularly suited for studying diseases that predominantly affect middle-aged and older adults, the Montgomery dataset allows for broader generalization across diverse age demographics.