AIMC Topic: Risk Factors

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Prediction of the 10-year incidence of type 2 diabetes mellitus based on advanced anthropometric indices using machine learning methods in the Iranian population.

Diabetes research and clinical practice
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a growing chronic disease that can lead to disability and early death. This study aimed to establish a predictive model for the 10-year incidence of T2DM based on novel anthropometric indices.

A simple machine learning model for the prediction of acute kidney injury following noncardiac surgery in geriatric patients: a prospective cohort study.

BMC geriatrics
BACKGROUND: Surgery in geriatric patients often poses risk of major postoperative complications. Acute kidney injury (AKI) is a common complication following noncardiac surgery and is associated with increased mortality. Early identification of geria...

Deep learning model for the prediction of all-cause mortality among long term care people in China: a prospective cohort study.

Scientific reports
This study aimed to develop a deep learning model to predict the risk stratification of all-cause death for older people with disability, providing guidance for long-term care plans. Based on the government-led long-term care insurance program in a p...

Prediction of hepatic metastasis in esophageal cancer based on machine learning.

Scientific reports
This study aimed to establish a machine learning (ML) model for predicting hepatic metastasis in esophageal cancer. We retrospectively analyzed patients with esophageal cancer recorded in the Surveillance, Epidemiology, and End Results (SEER) databas...

Determination of prognostic markers for COVID-19 disease severity using routine blood tests and machine learning.

Anais da Academia Brasileira de Ciencias
The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients' care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This ...

Black-white differences in chronic stress exposures to predict preterm birth: interpretable, race/ethnicity-specific machine learning model.

BMC pregnancy and childbirth
BACKGROUND: Differential exposure to chronic stressors by race/ethnicity may help explain Black-White inequalities in rates of preterm birth. However, researchers have not investigated the cumulative, interactive, and population-specific nature of ch...

Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers.

Scientific reports
Type II diabetes mellitus (T2DM) is a rising global health burden due to its rapidly increasing prevalence worldwide, and can result in serious complications. Therefore, it is of utmost importance to identify individuals at risk as early as possible ...

Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach.

Cardiovascular diabetology
BACKGROUND: Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as...

Development and validation of machine learning models to predict perioperative transfusion risk for hip fractures in the elderly.

Annals of medicine
BACKGROUND: Patients with hip fractures frequently need to receive perioperative transfusions of concentrated red blood cells due to preoperative anemia or surgical blood loss. However, the use of perioperative blood products increases the risk of ad...