Prediction of Sepsis Progression in Critical Illness Using Artificial Neural Network

• Main Authors: F. M., Suhaimi, J. G., Chase, G. M., Shaw, Ummu Kulthum, Jamaludin, Normy Norfiza, A. Razak
• Other Authors: Fatimah, Ibrahim
• Format: Book Section
• Language: English
• Published: Springer 2016
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/11575/1/Prediction%20of%20Sepsis%20Progression%20in%20Critical%20Illness%20Using%20Artificial%20Neural%20Network.pdf; http://umpir.ump.edu.my/id/eprint/11575/; http://dx.doi.org/10.1007/978-981-10-0266-3_26
• Institution: Universiti Malaysia Pahang

Early treatment of sepsis can reduce mortality and improve a patient condition. However, the lack of clear information and accurate methods of diagnosing sepsis at an early stage makes it become a significant challenge. The decision to start, continue or stop antimicrobial therapy is normally base o...