AI-driven visualization tool for analyzing data and predicting drug-resistant outbreaks

A tool was developed to identify potential disease outbreaks using pathogen and serotype data. By analyzing isolate numbers and comparing them to a two-year average, the tool highlights anomalies suggestive of outbreaks. When applied to Salmonella data, it revealed potential outbreaks related to spe...

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Veröffentlicht in:Drug resistance updates Jg. 78; S. 101174
1. Verfasser: Takefuji, Yoshiyasu
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Scotland Elsevier Ltd 01.01.2025
Schlagworte:
Anti-Bacterial Agents - pharmacology
Artificial Intelligence
CDC dataset
Disease Outbreaks
Drug Resistance, Bacterial
Generative AI
Humans
Outbreak visualization
Pathogen and serotype
Salmonella - drug effects
Salmonella - isolation & purification
Salmonella Infections - epidemiology
Salmonella Infections - microbiology
Serogroup
Generative AI
Pathogen and serotype
CDC dataset
Outbreak visualization
ISSN:1368-7646, 1532-2084, 1532-2084
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:A tool was developed to identify potential disease outbreaks using pathogen and serotype data. By analyzing isolate numbers and comparing them to a two-year average, the tool highlights anomalies suggestive of outbreaks. When applied to Salmonella data, it revealed potential outbreaks related to specific serotypes.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Correspondence-3
content type line 23
ISSN:1368-7646
1532-2084
1532-2084
DOI:10.1016/j.drup.2024.101174