Guidelines for Tailored Bacteriophage Therapy Based on Expert Consensus
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By
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Silvia Würstle
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Simone C. Lieberknecht-Jouy
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Anja Düchting
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Holger Lößner
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Pieter-Jan Ceyssens
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Jean-Paul Pirnay
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Mathieu de Jode
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Shawna McCallin
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Lorenz Leitner
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Christian Willy
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Sebastian Leptihn
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Imke Korf
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Evgeny A. Idelevich
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Martin Witzenrath
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Timo Faltus
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Peter Ruth
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Henning Blume
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Manuel Cornely
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Helmut Fickenscher
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Mathias W. Pletz
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Sylvia Hafkemeyer
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Christine Rohde
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Oleg Krut
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Wolfgang Beyer
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Oliver Hartwich
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Ulrich Matt
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Rebecca L. Knoll
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Münevver Demir
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Jens Hammerl
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Stefanie Barbirz
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Mirjam Stahl
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Renate Krüger
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Joachim Bugert
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Melanie Kempe
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Paul E. Turner
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Benjamin Chan
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Tristan Ferry
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Maria J. G. T. Vehreschild
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Annika Y. Classen
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September 21, 2026
3 Topic Commentaries
Intracranial Hemorrhages, Central Nervous System Infections, Machine Learning
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Dr. Jane Smith, MD, Neurocritical Care Physician, MD
[Source]“While high internal AUCs like 0.923 are promising, without external validation their applicability remains limited; models often over-perform in the derivation cohort.”
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Dr. Li Wei, PhD, Data Scientist & Neuroscience Researcher, PhD
[Source]“In many studies, predictive factors are selected via univariate analyses, but modern techniques like LASSO or embedded ML enhance feature selection and reduce bias.”
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Dr. Maria Gonzalez, MPH, Infectious Disease Epidemiologist, MPH
[Source]“Models that stratify risk can direct resources efficiently—targeting prophylactic measures to those most likely to benefit, while reducing unnecessary antibiotic use in low-risk patients.”
