Disparities in diagnostic access continue to define health system inequities across low- and middle-income countries, where both cancer and infectious diseases contribute disproportionately to preventable morbidity and mortality. Despite advances in biomarker discovery and therapeutic precision, diagnostic infrastructure remains centralized, fragmented, and often disconnected from clinical environments where decisions must be made. This dissertation addresses these systemic constraints through the development of multiplexed, analytically rigorous diagnostic platforms designed for decentralized implementation. The first study presents a quantitative lateral flow immunoassay for breast cancer molecular subtyping. Designed to detect estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2 simultaneously, the assay leverages europium-based fluorescence and spatially separated test lines to enable sensitive and specific biomarker quantification. Integrated with a portable imaging and computation system, the platform supports automated test-to-control normalization and subtype classification using threshold-based interpretation. Comparative benchmarking against enzyme-linked immunosorbent assay demonstrates its capacity to resolve clinically actionable subtypes, offering a viable alternative to immunohistochemistry in settings without access to histopathology. The second study introduces a duplex lateral flow immunoassay for simultaneous detection of Ebola virus and Lassa virus antigens. Chromatically distinct nanoparticle conjugates and channel-separated image acquisition enable multiplexed detection on a single membrane without signal interference. Analytical sensitivity, lineage specificity, and inter-laboratory reproducibility were validated through blinded testing, including evaluation with biosafety-level-validated viral preparations in collaboration with the United States Army Medical Research Institute of Infectious Diseases. These results support the platform’s relevance for outbreak surveillance and community-level pathogen screening. The third component provides a systems-level review of emerging diagnostic strategies for oncology in resource-constrained environments. It evaluates innovations in multiplexed protein detection, nucleic acid amplification, portable imaging, and machine learning–assisted interpretation, while identifying translational challenges related to cold-chain requirements, regulatory asymmetry, and data representativeness. This analysis positions diagnostic design within broader delivery frameworks and emphasizes the conditions required for equitable integration. Together, these studies define a coherent translational model for diagnostic innovation. By aligning assay engineering with quantitative imaging and deployment strategy, this work advances scientifically rigorous and context-responsive platforms for improving diagnostic equity in underserved settings.