AIMC Topic: Incidence
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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
Jun 25, 2024
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.
Development of machine learning models for patients in the high intrahepatic cholangiocarcinoma incidence age group.
BMC geriatrics
Jun 25, 2024
BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) has a poor prognosis and is understudied. Based on the clinical features of patients with ICC, we constructed machine learning models to understand their importance on survival and to accurately deter...
Predicting chronic wasting disease in white-tailed deer at the county scale using machine learning.
Scientific reports
Jun 22, 2024
Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively impacts populations, erodes wildlife conservation, drains resource dollars, and challenges wildlife management agencies. Risk factors for CWD have been investigate...
Predicting the onset of overweight in Chinese high school students: a machine-learning approach in a one-year prospective cohort study.
Endocrine
Jun 10, 2024
OBJECTIVE: This study aimed to develop and evaluate machine-learning models for predicting the onset of overweight in adolescents aged 14‒17, utilizing easily collectible personal information.
Fine-Scale Spatial Prediction on the Risk of Infection in the Republic of Korea.
Journal of Korean medical science
Jun 10, 2024
BACKGROUND: Malaria elimination strategies in the Republic of Korea (ROK) have decreased malaria incidence but face challenges due to delayed case detection and response. To improve this, machine learning models for predicting malaria, focusing on hi...
Identifying subtypes of type 2 diabetes mellitus with machine learning: development, internal validation, prognostic validation and medication burden in linked electronic health records in 420 448 individuals.
BMJ open diabetes research & care
Jun 4, 2024
INTRODUCTION: None of the studies of type 2 diabetes (T2D) subtyping to date have used linked population-level data for incident and prevalent T2D, incorporating a diverse set of variables, explainable methods for cluster characterization, or adhered...
Machine Learning-Based Prediction Models for Clostridioides difficile Infection: A Systematic Review.
Clinical and translational gastroenterology
Jun 1, 2024
INTRODUCTION: Despite research efforts, predicting Clostridioides difficile incidence and its outcomes remains challenging. The aim of this systematic review was to evaluate the performance of machine learning (ML) models in predicting C. difficile i...
Interpretable machine learning models for predicting the incidence of antibiotic- associated diarrhea in elderly ICU patients.
BMC geriatrics
May 24, 2024
BACKGROUND: Antibiotic-associated diarrhea (AAD) can prolong hospitalization, increase medical costs, and even lead to higher mortality rates. Therefore, it is essential to predict the incidence of AAD in elderly intensive care unit(ICU) patients. Th...
A Novel Deep Learning Approach for Forecasting Myocardial Infarction Occurrences with Time Series Patient Data.
Journal of medical systems
May 22, 2024
Myocardial Infarction (MI) commonly referred to as a heart attack, results from the abrupt obstruction of blood supply to a section of the heart muscle, leading to the deterioration or death of the affected tissue due to a lack of oxygen. MI, poses a...
Artificial Intelligence for Urology Research: The Holy Grail of Data Science or Pandora's Box of Misinformation?
Journal of endourology
May 15, 2024
Artificial intelligence tools such as the large language models (LLMs) Bard and ChatGPT have generated significant research interest. Utilization of these LLMs to study the epidemiology of a target population could benefit urologists. We investigate...
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