TY  -  JOUR
AU  -  Zovi, Andrea
AU  -  Polito, Giacomo
AU  -  Caprodossi, Andrea
AU  -  Sabbatucci, Michela
AU  -  Sorrentino, Rosario
AU  -  Vitiello, Antonio
T1  -  Strategies in using artificial intelligence to combat antimicrobial resistance
PY  -  2025
Y1  -  2025-03-01
DO  -  10.1701/4460.44557
JO  -  Recenti Progressi in Medicina
JA  -  Recenti Prog Med
VL  -  116
IS  -  3
SP  -  168
EP  -  174
PB  -  Il Pensiero Scientifico Editore
SN  -  2038-1840
Y2  -  2026/04/16
UR  -  http://dx.doi.org/10.1701/4460.44557
N2  -  Summary. Infectious diseases caused by pathogens resistant to antimicrobial treatments, defined as antimicrobial resistance (AMR), are a serious global health crisis, considered among the main threats to global public health according to the World Health Organization. New forms of advanced information technology are receiving global consideration as a help in countering this health threat, like Artificial Intelligence (AI). Applications of AI in healthcare could help in reducing the time needed to discover new antimicrobial drugs, improving the accuracy and timing of surveillance, diagnosis, and treatment, while reducing expenses. AI is now proposed as a valuable and potential help for different sectors of the health world. In this short review, we will consider the recent evidence supporting the important role that AI can play in countering the phenomenon of AMR.
ER  -