Maximum values of accuracy for the Biometec dataset when using only resistance genes or when using both resistance and virulence genes.

Maximum values of accuracy for the Biometec dataset when using only resistance genes or when using both resistance and virulence genes.

<p>The results include the six antimicrobial agents common to the public dataset, and the four antimicrobial agents present only in the Biometec dataset.</p>

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Chiara Condorelli (19697665) (author)
مؤلفون آخرون: Emanuele Nicitra (19697668) (author), Nicolò Musso (6101027) (author), Dafne Bongiorno (14330361) (author), Stefania Stefani (188822) (author), Lucia Valentina Gambuzza (19697671) (author), Vincenza Carchiolo (17797569) (author), Mattia Frasca (19697674) (author)
منشور في: 2024
الموضوعات:
Medicine
Microbiology
Pharmacology
Biotechnology
Infectious Diseases
Virology
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Information Systems not elsewhere classified
making infections challenging
klebsiella pneumoniae </
div >< p
predicting antibiotic resistance
drug resistance heightens
antimicrobial drugs ineffective
predict antimicrobial resistance
antimicrobial resistance occurs
treat infectious diseases
machine learning techniques
bacterial genomic data
resistance renders antibiotics
antimicrobial resistance
machine learning
genomic data
support clinicians
severe illness
pathogen genomes
medications employed
longer respond
genome composition
gene content
even thousands
disease spread
containing hundreds
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الوصف
الملخص:<p>The results include the six antimicrobial agents common to the public dataset, and the four antimicrobial agents present only in the Biometec dataset.</p>

مواد مشابهة