ABSTRACT
The application of artificial intelligence in medicine has gradually received attention along with its development. Many studies have shown that machine learning has a wide range of applications in stomatology, especially in the clinical diagnosis and treatment of maxillofacial cysts and tumors. This article reviews the application of machine learning in maxillofacial cyst and tumor to provide a new method for the diagnosis of oral and maxillofacial diseases.
Subject(s)
Humans , Artificial Intelligence , Cysts/diagnosis , Machine Learning , Oral MedicineABSTRACT
<p><b>OBJECTIVE</b>Sepsis is defined as life-threatening organ dysfunction due to a dysregulated host response to infection. In this article, we reviewed the correlation between neutrophil dysfunction and sepsis.</p><p><b>DATA SOURCES</b>Articles published up to May 31, 2016, were selected from the PubMed databases, with the keywords of "neutrophil function", "neutrophil dysfunction", and "sepsis".</p><p><b>STUDY SELECTION</b>Articles were obtained and reviewed to analyze the neutrophil function in infection and neutrophil dysfunction in sepsis.</p><p><b>RESULTS</b>We emphasized the diagnosis of sepsis and its limitations. Pathophysiological mechanisms involve a generalized circulatory, immune, coagulopathic, and/or neuroendocrine response to infection. Many studies focused on neutrophil burst or cytokines. Complement activation, impairment of neutrophil migration, and endothelial lesions are involved in this progress. Alterations of cytokines, chemokines, and other mediators contribute to neutrophil dysfunction in sepsis.</p><p><b>CONCLUSIONS</b>Sepsis represents a severe derangement of the immune response to infection, resulting in neutrophil dysfunction. Neutrophil dysfunction promotes sepsis and even leads to organ failure. Mechanism studies, clinical practice, and strategies to interrupt dysregulated neutrophil function in sepsis are desperately needed.</p>