Artificial Intelligence Techniques for Monitoring Dangerous Infections [Електронний ресурс] / Evelina Lamma, Paola Mello, Anna Nanetti и др. // IEEE Transactions on Information Technology in Biomedicine [Электронный ресурс]. – 2006. – № 1. – Pp. 143 – 155
- Електронна версія (pdf / 275 Kb)
Статистика використання: Завантажень: 8
Анотація:
The monitoring and detection of nosocomial infections is a very important problem arising in hospitals. A hospitalacquired or nosocomial infection is a disease that develops after
admission into the hospital and it is the consequence of a treatment, not necessarily a surgical one, performed by the medical staff. Nosocomial infections are dangerous because they are caused by bacteria which have dangerous (critical) resistance to antibiotics. This problem is very serious all over the world. In Italy, almost 5–8% of the patients admitted into hospitals develop this kind of infection. In order to reduce this figure, policies for controlling infections should be adopted by medical practitioners. In order to support them in this complex task, we have developed a system, calledMERCURIO, capable ofmanaging different aspects of the problem. The objectives of this system are the validation of microbiological data and the creation of a real time epidemiological
information system. The system is useful for labo
admission into the hospital and it is the consequence of a treatment, not necessarily a surgical one, performed by the medical staff. Nosocomial infections are dangerous because they are caused by bacteria which have dangerous (critical) resistance to antibiotics. This problem is very serious all over the world. In Italy, almost 5–8% of the patients admitted into hospitals develop this kind of infection. In order to reduce this figure, policies for controlling infections should be adopted by medical practitioners. In order to support them in this complex task, we have developed a system, calledMERCURIO, capable ofmanaging different aspects of the problem. The objectives of this system are the validation of microbiological data and the creation of a real time epidemiological
information system. The system is useful for labo