AIMC Topic: Risk Factors

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Tree-Based Machine Learning to Identify Predictors of Psoriasis Incidence at the Neighborhood Level: A Populational Study from Quebec, Canada.

American journal of clinical dermatology
BACKGROUND: Psoriasis is a major global health burden affecting ~ 60 million people worldwide. Existing studies on psoriasis focused on individual-level health behaviors (e.g. diet, alcohol consumption, smoking, exercise) and characteristics as drive...

A new model using deep learning to predict recurrence after surgical resection of lung adenocarcinoma.

Scientific reports
This study aimed to develop a deep learning (DL) model for predicting the recurrence risk of lung adenocarcinoma (LUAD) based on its histopathological features. Clinicopathological data and whole slide images from 164 LUAD cases were collected and us...

Artificial-intelligence-based risk prediction and mechanism discovery for atrial fibrillation using heart beat-to-beat intervals.

Med (New York, N.Y.)
BACKGROUND: Early diagnosis of atrial fibrillation (AF) is important for preventing stroke and other complications. Predicting AF risk in advance can improve early diagnostic efficiency. Deep learning has been used for disease risk prediction; howeve...

Machine Learning Did Not Outperform Conventional Competing Risk Modeling to Predict Revision Arthroplasty.

Clinical orthopaedics and related research
BACKGROUND: Estimating the risk of revision after arthroplasty could inform patient and surgeon decision-making. However, there is a lack of well-performing prediction models assisting in this task, which may be due to current conventional modeling a...

Prevalence and Risk Factors of Chronic Kidney Disease in the General Population in Abidjan, Côte d'Ivoire: A Cross-sectional Study.

Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Chronic kidney disease (CKD) is a major cause of morbidity and mortality worldwide, but few studies are available on CKD in Cote d'Ivoire. We aimed to assess the prevalence of CKD and identify its associated factors in the general population in Abidj...

Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach.

Journal of endocrinological investigation
BACKGROUND: Gestational diabetes mellitus (GDM) is a serious health concern that affects pregnant women worldwide and can lead to adverse pregnancy outcomes. Early detection of high-risk individuals and the implementation of appropriate treatment can...

ChatGPT and Patients With Heart Failure.

Angiology
ChatGPT (Generative Pre-trained Transformer) is a large-scale language processing model, with possibilities for professional patient support in a patient-friendly way. The aim of the study was to examine the accuracy and reproducibility of ChatGPT in...

Artificial intelligence in preventive cardiology.

Progress in cardiovascular diseases
Artificial intelligence (AI) is a field of study that strives to replicate aspects of human intelligence into machines. Preventive cardiology, a subspeciality of cardiovascular (CV) medicine, aims to target and mitigate known risk factors for CV dise...

Development of a machine learning-based model for predicting individual responses to antihypertensive treatments.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: Personalized antihypertensive drug selection is essential for optimizing hypertension management. The study aimed to develop a machine learning (ML) model to predict individual blood pressure (BP) responses to different antihyper...