AIMC Topic: Risk Assessment

Clear Filters Showing 2361 to 2370 of 2930 articles

Risk Prediction of Low Bone Density in Elderly Patients with Supervised Machine Learning Algorithms.

Balkan medical journal
BACKGROUND: Low bone mineral density (BMD) is a common age-related condition that elevates the risk of fractures and mortality. Machine learning (ML) techniques offer a promising approach for early prediction using readily available clinical, biochem...

Sex-specific prognostic value of automated epicardial adipose tissue quantification on serial lung cancer screening chest computed tomography.

European heart journal. Cardiovascular Imaging
AIMS: Epicardial adipose tissue (EAT) is a metabolically active fat depot associated with coronary atherosclerosis and cardiovascular (CV) risk. While EAT is a known prognostic marker in lung cancer screening, its sex-specific prognostic value remain...

Prediction of mortality in cancer patients with COVID-19 using machine learning methods.

Medicine
This study aimed to predict mortality in cancer patients diagnosed with COVID-19 using machine learning (ML) algorithms and identify the clinical and laboratory parameters associated with mortality. Demographic, clinical, and laboratory data of cance...

External validation of an AI-based preoperative frailty index using real-world data.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Preoperative frailty assessment is crucial for surgical risk stratification in older adults. Traditional frailty measurements are often too time-consuming and resource-intensive in preoperative settings. This study aimed to externally val...

Development and external validation of a prediction model for prolonged intensive care unit stay in heart failure patients.

European journal of cardiovascular nursing
AIMS: Prolonged intensive care unit (ICU) stays in heart failure patients are associated with poor prognosis and result in high medical expenses. To develop and validate a predictive model for prolonged ICU stays in heart failure patients.

[Research on risk prediction of acute respiratory distress syndrome complicated with acute kidney injury: progress and challenges].

Zhonghua yi xue za zhi
The risk of acute respiratory distress syndrome (ARDS) combined with acute kidney injury (AKI) is high and the prognosis is poor. Therefore, there is an urgent need for efficient and accurate methods to improve clinical doctors' early diagnosis and p...

Machine Learning-Based Flap Takeback Prediction Modeling: Theory for a Real-Time, Patient-Specific Postoperative Flap Monitoring and Alert System.

Microsurgery
BACKGROUND: Postoperative free flap monitoring is crucial yet taxing, requiring frequent and often subjective assessments to detect early signs of compromise. The present study aims to develop a machine learning model to predict the risk of flap take...

How can machine learning inform about chemical risks in circular textiles?

Integrated environmental assessment and management
Hazardous chemicals in textiles represent a serious health issue. This is mainly due to missing data on the used chemicals and/or on their hazard, which prevents proper chemical risk assessment. Although identifying and filling these data gaps is cru...

Prediction model for postoperative urinary retention in patients undergoing totally extraperitoneal groin hernia repair.

Surgery
BACKGROUND: Postoperative urinary retention remains a common complication after totally extraperitoneal groin hernia repair, often prolonging hospitalization and increasing patient discomfort. This study aimed to develop a prediction model using mach...

Improving risk assessment of local failure in brain metastases patients using vision transformers - A multicentric development and validation study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: This study investigates the use of Vision Transformers (ViTs) to predict Freedom from Local Failure (FFLF) in patients with brain metastases using pre-operative MRI scans. The goal is to develop a model that enhances risk stra...