AIMC Topic: Risk Assessment

Clear Filters Showing 1821 to 1830 of 2930 articles

Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Internal and emergency medicine
Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential for effective patient allocation and management. To predict patient risk for critical COVID-19 base...

Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations.

International journal of environmental research and public health
Suicide is a leading cause of death that defies prediction and challenges prevention efforts worldwide. Artificial intelligence (AI) and machine learning (ML) have emerged as a means of investigating large datasets to enhance risk detection. A system...

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

Surgery
BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for hepatocellular carcinoma and is the leading cause of postoperative mortality. Recommendations for hepatectomy for hepatocellular carcinoma are based on ...

Machine Learning Model for Risk Prediction of Community-Acquired Acute Kidney Injury Hospitalization From Electronic Health Records: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Community-acquired acute kidney injury (CA-AKI)-associated hospitalizations impose significant health care needs and contribute to in-hospital mortality. However, most risk prediction models developed to date have focused on AKI in a spec...

Development and validation of prognosis model of mortality risk in patients with COVID-19.

Epidemiology and infection
This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective study of the inpatients with COVID-19 admitted from 15 January to 15 Mar...

PSA-based machine learning model improves prostate cancer risk stratification in a screening population.

World journal of urology
CONTEXT: The majority of prostate cancer diagnoses are facilitated by testing serum Prostate Specific Antigen (PSA) levels. Despite this, there are limitations to the diagnostic accuracy of PSA. Consideration of patient demographic factors and bioche...

Development of a Machine Learning Model for Survival Risk Stratification of Patients With Advanced Oral Cancer.

JAMA network open
IMPORTANCE: A tool for precisely stratifying postoperative patients with advanced oral cancer is crucial for the treatment plan, such as intensifying or deintensifying the regimen to improve their quality of life and prognosis.