## 1 Introduction  
Pediatric pneumonia constitutes a significant global health challenge, with a disproportionate impact on low- and middle-income countries (LMICs) [1], where it persists as a primary cause of mortality in children under five years of age [2]. According to the World Health Organization (WHO), pneumonia is responsible for approximately 14% of all fatalities in children under five years old; this translates to an estimated 740,000 deaths each year [3]. Globally, the disease accounts for 10-20 million hospitalizations and an annual incidence of 150-156 million cases, with over 80% of pneumonia-related deaths occurring in LMICs. Regions such as South Asia and West and Central Africa bear the highest burden, with pneumonia affecting approximately 1 in 71 children annually [4, 5]. This infectious disease, characterized by inflammation of the pulmonary alveoli in one or both lungs, presents clinically in children with a spectrum of signs and symptoms, including cough, fever, dyspnea, and chest pain [6]. In severe presentations, the disease can progress to hypoxemia (decreased arterial oxygen saturation) and potentially life-threatening complications such as pleural effusion and respiratory failure [7]. The etiology of pediatric pneumonia is diverse, encompassing bacterial, viral, and fungal pathogens. While the clinical presentation may exhibit variability based on the specific causative agent, the disease typically manifests with respiratory distress and systemic symptoms, necessitating timely diagnosis and appropriate therapeutic intervention [8; 9]. In high-income countries, the mortality rates are significantly lower due to better access to vaccines, diagnostic tools, and antibiotics. However, pneumonia continues to impose a significant burden on healthcare systems worldwide, accounting for millions of outpatient visits and hospital admissions annually, as well as substantial healthcare costs. The financial burden of prolonged care is particularly severe in resource-constrained areas, where limited access to affordable healthcare exacerbates the issue [10; 11]. Addressing this challenge requires not only improvements in prevention and treatment but also innovative diagnostic methods to ensure early and accurate detection [12]. Deep learning has become a pivotal tool in the diagnosis of pediatric pneumonia, offering advanced capabilities for analyzing large datasets of medical images. These algorithms can identify subtle patterns and anomalies that may elude human interpretation, providing consistent and objective diagnostic outcomes [13]. By reducing diagnostic errors and operating with greater efficiency than traditional methods, deep learning addresses key limitations of conventional approaches. Specifically, conventional methods often rely on manual interpretation, which can be prone to human error and variability, particularly when identifying subtle or atypical patterns in medical images. Deep learning overcomes these challenges by leveraging automated feature extraction and pattern recognition, enabling consistent and reproducible results. Additionally, traditional diagnostic methods can struggle with large volumes of data or complex datasets, whereas deep learning excels at processing and analyzing such data efficiently [14]. Its utility is particularly pronounced in resource-constrained settings, where access to skilled radiologists and advanced diagnostic facilities is limited, thereby promoting equitable healthcare delivery and enabling timely, accurate diagnoses in underserved populations [15; 16]. CNNs, a specialized architecture within deep learning, have demonstrated remarkable accuracy in medical imaging. They excel at extracting and analyzing both local and global features from radiographic images, which are essential for identifying pathologies such as pneumonia [17]. In pediatric applications, deep learning models trained on extensive radiographic datasets can reliably detect features indicative of pneumonia, including those associated with early-stage or atypical presentations.