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

IF 15.8 1区 医学 Q1 PHARMACOLOGY & PHARMACY
Yoshiyasu Takefuji
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引用次数: 0

Abstract

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.
人工智能驱动的可视化工具,用于分析数据和预测耐药性爆发。
我们开发了一种工具,利用病原体和血清型数据来识别潜在的疾病爆发。通过分析分离物数量并将其与两年平均值进行比较,该工具可突出显示可能爆发疾病的异常情况。当应用于沙门氏菌数据时,它揭示了与特定血清型有关的潜在疫情爆发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Drug Resistance Updates
Drug Resistance Updates 医学-药学
CiteScore
26.20
自引率
11.90%
发文量
32
审稿时长
29 days
期刊介绍: Drug Resistance Updates serves as a platform for publishing original research, commentary, and expert reviews on significant advancements in drug resistance related to infectious diseases and cancer. It encompasses diverse disciplines such as molecular biology, biochemistry, cell biology, pharmacology, microbiology, preclinical therapeutics, oncology, and clinical medicine. The journal addresses both basic research and clinical aspects of drug resistance, providing insights into novel drugs and strategies to overcome resistance. Original research articles are welcomed, and review articles are authored by leaders in the field by invitation. Articles are written by leaders in the field, in response to an invitation from the Editors, and are peer-reviewed prior to publication. Articles are clear, readable, and up-to-date, suitable for a multidisciplinary readership and include schematic diagrams and other illustrations conveying the major points of the article. The goal is to highlight recent areas of growth and put them in perspective. *Expert reviews in clinical and basic drug resistance research in oncology and infectious disease *Describes emerging technologies and therapies, particularly those that overcome drug resistance *Emphasises common themes in microbial and cancer research
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