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.

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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
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article

Automated Protocol Pathogen Identification & Antimicrobial Susceptibility Profiling via Multi-Modal Data Fusion and HyperScore Evaluation

Zenodo (CERN European Organization for Nuclear Research)
Planetary Science and Exploration
article

Automated Protocol Pathogen Identification & Antimicrobial Susceptibility Profiling via Multi-Modal Data Fusion and HyperScore Evaluation

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Freed–Hardeman University (US)
Openalex Percentile: Top 49%
Planetary Science and Exploration
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