The role of biomarkers for detection of sepsis has come a long way. Molecular biomarkers are taking front stage at present, but machine learning and other computational measures using bigdata sets are promising. Clinical research in sepsis is hampered by lack of specificity of the diagnosis; sepsis is a syndrome with no uniformly agreed definition. This lack of diagnostic precision means there is no gold standard for this diagnosis. The final conclusion is expert opinion, which is not bad but not perfect. Perhaps machine learning will displace expert opinion as the final and most accurate definition for sepsis.
Keywords: Culture-independent; Host-derived biomarkers for early diagnosis of sepsis and septic shock; Machine-learning systems to identify susceptible patients with sepsis; Microbial diagnostic techniques; Rapid; Rapid genotypic and phenotypic methods to measure antimicrobial susceptibility patterns.
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