BACKGROUND: Identification of individuals at increased risk for suicide is an important public health priority, but the extent to which considering clinical phenomenology improves prediction of longer term outcomes remains understudied. Hospital disc...
OBJECTIVE: Sedation of neurocritically ill patients is one of the most challenging situation in ICUs. Quantitative knowledge on the sedation effect on brain activity in that complex scenario could help to uncover new markers for sedation assessment. ...
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Jan 29, 2019
OBJECTIVE: To apply a novel methodology with machine learning (ML) to a large national cancer registry to help identify patients who are high risk for delayed adjuvant radiation.
Improved methods are needed to risk stratify and predict outcomes in patients with primary sclerosing cholangitis (PSC). Therefore, we sought to derive and validate a prediction model and compare its performance to existing surrogate markers. The mod...
BACKGROUND: Identifying local recurrences in breast cancer from patient data sets is important for clinical research and practice. Developing a model using natural language processing and machine learning to identify local recurrences in breast cance...
BACKGROUND AND AIMS: The experience of alcohol use among adolescents is complex, with international differences in age of purchase and individual differences in consumption and consequences. This latter underlines the importance of prediction modelin...
BACKGROUND: The incidence of thyroid cancer is rising steadily because of overdiagnosis and overtreatment conferred by widespread use of sensitive imaging techniques for screening. This overall incidence growth is especially driven by increased diagn...
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