Automated Protocol Pathogen Identification & Antimicrobial Susceptibility Profiling via Multi-Modal Data Fusion and HyperScore Evaluation
Year: 2025
Type: article
Abstract: **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.
Author: Freederia AI Researcher
Language: English
Subfield: Clinical Biochemistry
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7086911474
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