scholarly journals Editorial: Clinical Application of Artificial Intelligence in Emergency and Critical Care Medicine, Volume I

2021 ◽  
Vol 8 ◽  
Author(s):  
Zhongheng Zhang ◽  
Nan Liu ◽  
Qinghe Meng ◽  
Longxiang Su
Keyword(s):  
Artificial Intelligence ◽  
Critical Care ◽  
Clinical Application ◽  
Critical Care Medicine

scholarly journals Critical Care, Critical Data

2019 ◽  
Vol 10 ◽  
pp. 117959721985656 ◽  
Author(s):  
Christopher V Cosgriff ◽  
Leo Anthony Celi ◽  
David J Stone
Keyword(s):  
Artificial Intelligence ◽  
Critical Care ◽  
Clinical Data ◽  
Continuous Monitoring ◽  
Data Science ◽  
Clinical Decision ◽  
Critical Care Medicine ◽  
Data Driven ◽  
Critical Data

As big data, machine learning, and artificial intelligence continue to penetrate into and transform many facets of our lives, we are witnessing the emergence of these powerful technologies within health care. The use and growth of these technologies has been contingent on the availability of reliable and usable data, a particularly robust resource in critical care medicine where continuous monitoring forms a key component of the infrastructure of care. The response to this opportunity has included the development of open databases for research and other purposes; the development of a collaborative form of clinical data science intended to fully leverage these data resources, and the creation of data-driven applications for purposes such as clinical decision support. Most recently, data levels have reached the thresholds required for the development of robust artificial intelligence features for clinical purposes. The systematic capture and analysis of clinical data in both individuals and populations allows us to begin to move toward precision medicine in the intensive care unit (ICU). In this perspective review, we examine the fundamental role of data as we present the current progress that has been made toward an artificial intelligence (AI)-supported, data-driven precision critical care medicine.

scholarly journals AI MSK clinical applications: spine imaging

2021 ◽  
Author(s):  
Florian A. Huber ◽  
Roman Guggenberger
Keyword(s):  
Artificial Intelligence ◽  
Clinical Application ◽  
Value Chain ◽  
Clinical Applications ◽  
Status Quo ◽  
Use Cases ◽  
Musculoskeletal Imaging ◽  
Future Perspective ◽  
Spine Imaging ◽  
The Status

AbstractRecent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain in spine imaging, independent from modality or specific application. This review aims to summarize the status quo and future perspective regarding utilization of AI for spine imaging. First, the basics of AI concepts are clarified. Second, the different tasks and use cases for AI applications in spine imaging are discussed and illustrated by examples. Finally, the authors of this review present their personal perception of AI in daily imaging and discuss future chances and challenges that come along with AI-based solutions.

scholarly journals Evaluation of Clinical Outcomes after Introduction of a Dedicated Infectious Diseases- Critical Care Medicine Service in Critical Care Units

2021 ◽  
Author(s):  
Polina Trachuk ◽  
Vagish Hemmige ◽  
Ruth Eisenberg ◽  
Kelsie Cowman ◽  
Victor Chen ◽  
...  
Keyword(s):  
Critical Care ◽  
Infectious Diseases ◽  
Clinical Outcomes ◽  
Broad Spectrum ◽  
Critical Care Medicine ◽  
Care Hospital ◽  
Intervention Period ◽  
Broad Spectrum Antibiotics ◽  
Antibiotic Utilization ◽  
The Impact

Abstract Objective Infection is a leading cause of admission to intensive care units (ICU), with critically ill patients often receiving empiric broad-spectrum antibiotics. Nevertheless, a dedicated infectious diseases (ID) consultation and stewardship team is not routinely established. An ID-Critical Care Medicine (ID-CCM) pilot program was designed at a 400-bed tertiary care hospital in which an ID attending was assigned to participate in daily rounds with the ICU team, as well as provide ID consultation on select patients. We sought to evaluate the impact of this dedicated ID program on antibiotic utilization and clinical outcomes in patients admitted to the ICU. Method In this single site retrospective study, we analyzed antibiotic utilization and clinical outcomes in patients admitted to an ICU during post-intervention period from January 1, 2017 to December 31, 2017 and compared it to antibiotic utilization in the same ICUs during the pre-intervention period from January 1, 2015 to December 31, 2015. Results Our data showed a statistically significant reduction in usage of most frequently prescribed antibiotics including vancomycin, piperacillin-tazobactam and cefepime during the intervention period. When compared to pre-intervention period there was no difference in-hospital mortality, hospital length of stay and re-admission. Conclusion With this multidisciplinary intervention, we saw a decrease in the use of the most frequently prescribed broad-spectrum antibiotics without a negative impact on clinical outcomes. Our study shows that the implementation of an ID-CCM service is a feasible way to promote antibiotic stewardship in the ICU and can be used as a strategy to reduce unnecessary patient exposure to broad-spectrum agents.

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