AIMC Topic: Predictive Value of Tests

Clear Filters Showing 2001 to 2010 of 2216 articles

Prediction of Prolonged Opioid Use After Surgery in Adolescents: Insights From Machine Learning.

Anesthesia and analgesia
BACKGROUND: Long-term opioid use has negative health care consequences. Patients who undergo surgery are at risk for prolonged opioid use after surgery (POUS). While risk factors have been previously identified, no methods currently exist to determin...

Stroke risk prediction using machine learning: a prospective cohort study of 0.5 million Chinese adults.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To compare Cox models, machine learning (ML), and ensemble models combining both approaches, for prediction of stroke risk in a prospective study of Chinese adults.

Machine learning-based integrative analysis of methylome and transcriptome identifies novel prognostic DNA methylation signature in uveal melanoma.

Briefings in bioinformatics
Uveal melanoma (UVM) is the most common primary intraocular human malignancy with a high mortality rate. Aberrant DNA methylation has rapidly emerged as a diagnostic and prognostic signature in many cancers. However, such DNA methylation signature av...

Large-scale mass spectrometry data combined with demographics analysis rapidly predicts methicillin resistance in Staphylococcus aureus.

Briefings in bioinformatics
BACKGROUND: A mass spectrometry-based assessment of methicillin resistance in Staphylococcus aureus would have huge potential in addressing fast and effective prediction of antibiotic resistance. Since delays in the traditional antibiotic susceptibil...

Prognostic outcome prediction by semi-supervised least squares classification.

Briefings in bioinformatics
Although great progress has been made in prognostic outcome prediction, small sample size remains a challenge in obtaining accurate and robust classifiers. We proposed the Rescaled linear square Regression based Least Squares Learning (RRLSL), a join...

An artificial neural network model to predict the mortality of COVID-19 patients using routine blood samples at the time of hospital admission: Development and validation study.

Medicine
BACKGROUND:: In a pandemic situation (e.g., COVID-19), the most important issue is to select patients at risk of high mortality at an early stage and to provide appropriate treatments. However, a few studies applied the model to predict in-hospital m...

Trauma outcome predictor: An artificial intelligence interactive smartphone tool to predict outcomes in trauma patients.

The journal of trauma and acute care surgery
BACKGROUND: Classic risk assessment tools often treat patients' risk factors as linear and additive. Clinical reality suggests that the presence of certain risk factors can alter the impact of other factors; in other words, risk modeling is not linea...

How machine learning is impacting research in atrial fibrillation: implications for risk prediction and future management.

Cardiovascular research
There has been an exponential growth of artificial intelligence (AI) and machine learning (ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has been mainly driven by the confluence of two factors: the advances ...

Machine Learning Algorithms Predict Functional Improvement After Hip Arthroscopy for Femoroacetabular Impingement Syndrome in Athletes.

The Journal of bone and joint surgery. American volume
BACKGROUND: Despite previous reports of improvements for athletes following hip arthroscopy for femoroacetabular impingement syndrome (FAIS), many do not achieve clinically relevant outcomes. The purpose of this study was to develop machine learning ...