Automated Protocol Pathogen Identification & Antimicrobial Susceptibility Profiling via Multi-Modal Data Fusion and HyperScore Evaluation
**Abstract:** This paper introduces a novel system, Automated Protocol Pathogen Identification & Antimicrobial Susceptibility Profiling (APP-ASPS), designed for rapid and accurate identification of bacterial pathogens and determination of their antimicrobial susceptibility profiles. APP-ASPS leverages a multi-modal approach integrating microscopy images, spectroscopic data (Raman/MALDI-TOF), phenotypic assay results, and genomic sequencing data. A rigorous evaluation pipeline, incorporating logical consistency checks, execution validation, novelty analysis, and impact forecasting – all fused via a HyperScore system – achieves unprecedented accuracy and efficiency. This system represents a significant advancement over traditional microbiology workflows, enabling faster diagnosis, personalized treatment strategies, and improved patient outcomes, with a commercially viable near-term roadmap.
Institutions
- Freed–Hardeman University (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-10-09
- DOI
- https://doi.org/10.5281/zenodo.17305513
- Primary Topic
- Planetary Science and Exploration
- Type
- article
- Field-Weighted Citation Impact
- 0.00