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1.
Nervenarzt ; 92(2): 115-126, 2021 Feb.
Article in German | MEDLINE | ID: mdl-33491152

ABSTRACT

Artificial intelligence (AI) has been introduced into medicine and an AI-assisted medicine will be the future that we should help to shape. In particular, supervised, unsupervised, and reinforcement learning will be the main methods to play a role in the implementation of AI. Severely ill patients admitted to the intensive care unit (ICU) are closely monitored in order to be able to quickly respond to any changes. These monitoring data can be used to train AI models to predict critical phases in advance, making an earlier reaction possible. To achieve this a large amount of clinical data are needed in order to train models and an external validation on independent cohorts should take place. Prospective studies with treatment of patients admitted to the ICU with AI assistance should show that they provide a benefit for patients. We present the most important resources from de-identified (anonymized) patient data on open-source use for AI research in intensive care medicine. The focus is on neurological diseases in the ICU, therefore, we provide an overview of existing models for prediction of outcome, vasospasms, intracranial pressure and levels of consciousness. To introduce the advantages of AI in the clinical routine, more AI-based models with larger datasets will be needed. To achieve this international cooperation is absolutely necessary. Clinical centers associated with universities are needed to provide a constant validation of applied models as these models can change during use or a bias can develop during the training. A strong commitment to AI research is important for Germany, not only with respect to academic achievements but also in the light of a rapidly growing influence of AI on the economy.


Subject(s)
Artificial Intelligence , Intensive Care Units , Critical Care , Humans , Monitoring, Physiologic , Prospective Studies
2.
J Neuroendocrinol ; 24(1): 174-82, 2012 Jan.
Article in English | MEDLINE | ID: mdl-21615563

ABSTRACT

Glucocorticoids (GCs) are widely used to treat inflammatory diseases such as multiple sclerosis (MS). They predominantly act through the GC receptor, a member of the nuclear receptor superfamily that controls transcription by several different mechanisms. Owing to its ubiquitous expression, there are a variety of cell types that could serve as GC targets in the pathogenesis and treatment of MS. This brings about a great diversity of mechanisms potentially involved in the modulation of neuroinflammation by GCs, including the induction of apoptosis, repression of pro-inflammatory mediators and the expansion of myeloid-derived suppressor cells. Nevertheless, it is not well understood which of these mechanisms are essential for therapeutic efficacy. In this review, we summarise findings made concerning the actions of GCs in MS and its animal model experimental autoimmune encephalomyelitis, and also elucidate current concepts and developments that pertain to this clinically highly relevant treatment regimen.


Subject(s)
Encephalitis/metabolism , Encephalomyelitis, Autoimmune, Experimental/metabolism , Glucocorticoids/metabolism , Receptors, Glucocorticoid/metabolism , Animals , Apoptosis/physiology , Inflammation Mediators/metabolism , Mice , T-Lymphocytes/metabolism
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