OBJECTIVES: Early detection of sepsis is critical in clinical practice since each hour of delayed treatment has been associated with an increase in mortality due to irreversible organ damage. This study aimed to develop an explainable artificial inte...
BACKGROUND: Accurate diagnostic strategies to identify SARS-CoV-2 positive individuals rapidly for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PC...
OBJECTIVES: Bacteremia and fungemia can cause life-threatening illness with high mortality rates, which increase with delays in antimicrobial therapy. The objective of this study is to develop machine learning models to predict blood culture results ...
RATIONALE: Computer-assisted detection (CAD) systems based on artificial intelligence (AI) using convolutional neural network (CNN) have been successfully used for the diagnosis of unruptured cerebral aneurysms in experimental situations. However, it...
The journals of gerontology. Series B, Psychological sciences and social sciences
Oct 16, 2020
OBJECTIVES: Socially assistive robots (SARs) need to be studied from older adults' perspective, given their predicted future ubiquity in aged-care settings. Current ethical discourses on SARs in aged care are uninformed by primary stakeholders' ethic...
OBJECTIVES: To evaluate the utility of machine learning (ML) for the management of Medicare beneficiaries at risk of severe respiratory infections in community and postacute settings by (1) identifying individuals in a community setting at risk of in...
This cross-sectional study applies natural language processing to electronic health records from a large health care delivery system to examine performance status documentation among patients newly diagnosed with colorectal cancer.
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