Complex diseases, such as sepsis and cancer, often involve intricate interactions between different biological systems, necessitating diagnostic tools that can analyze multiple biomarkers simultaneously. This is particularly urgent in sepsis, a dynamic syndrome driven by host–pathogen interactions, where current tools often fail to quickly and accurately assess both the host's immune response and the presence of viable pathogens. Most existing technologies are limited to either pathogen detection or host-response monitoring, missing the two-way signaling between host and pathogens that defines septic pathophysiology. Here, we present MIDAS (Multiplexed Intelligent Diffraction Analysis System), a new assay platform that enables the integrated analysis of the host–pathogen interface by quantifying both bacterial RNA markers for pathogen detection and phenotyping, as well as host inflammatory proteins, within a single system in under 4 h, significantly reducing the turnaround time for pathogen identification by over 20-40 h compared to standard culture workflows. MIDAS synergistically integrates (i) digital holography for high-throughput imaging, (ii) shape-encoded hydrogel sensor arrays for high multiplexing, and (iii) deep learning for fast, automated image analysis—all optimized for point-of-care use in low resource settings. In this proof-of-concept study with two sets of markers—5 bacterial species and 5 plasma proteins—MIDAS demonstrated superior performance in detection sensitivity/specificity, multiplexing power, and speed, compared to standard methods (ELISA, culture, qPCR), making it a powerful diagnostic tool for sepsis. Its modular design allows for expansion beyond the initial sensor elements and marker panels selected in this study. This generic platform, in conjunction with its single-cell analysis capabilities, could serve as a highly multiplexable solution for a variety of applications.