AIMC Topic: Body Mass Index

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First trimester prediction of gestational diabetes mellitus by machine learning in twin pregnancies.

Archives of gynecology and obstetrics
INTRODUCTION: We aimed to develop a machine learning model for first-trimester prediction of gestational diabetes mellitus (GDM) in twin pregnancies using a prospective international, multi-center cohort and identify useful predictive markers. METHOD...

Integrating inflammatory biomarkers and demographic variables with machine learning to predict endometriosis risk.

Scientific reports
This study explores the relationship between inflammatory biomarkers and the risk of endometriosis, aiming to develop a predictive model using National Health and Nutrition Examination Survey (1999-2006) data. The dataset included 4,089 females with ...

Aetiological clustering of newly diagnosed type 2 diabetes using machine learning: a retrospective cross-sectional study in Dubai, UAE.

BMJ open
OBJECTIVES: Type 2 diabetes (T2D) is a complex disease with a heterogeneous clinical presentation. Recently, five distinct clusters of T2D have been identified in the Emirati population of long-standing T2D with complications. This study aimed to val...

A neural network approach to sarcopenia prediction based on bioelectrical impedance in community-dwelling older adults.

PloS one
This study aimed to apply a neural network to raw bioelectrical impedance analysis data and to test whether sarcopenia could be predicted with high accuracy. The study population comprised 727 community-dwelling older adults aged 65-85 years who part...

The exhaled breath pattern as a potential method for biometrics identification.

Scientific reports
Conventional biometric identification methods relying on Personally Identifiable Information (PII) pose significant challenges concerning privacy and security. Volatile organic compounds (VOCs) in exhaled breath are unique to individuals and can serv...

Deep Learning Predicts Cardiac Output from Seismocardiographic Signals in Heart Failure.

The American journal of cardiology
Determination of cardiac output (CO) is essential to the clinical management of cardiovascular compromise. However, the invasiveness, procedural risks, and reliance on specialized infrastructure limit accessibility and scalability of standard-of-care...

AI-driven bone mineral density prediction from chest x-rays and its association with obstructive sleep apnea.

PloS one
With an increasing aging population, the prevalence of chronic comorbidities is on the rise. The potential relationship between obstructive sleep apnea (OSA) and osteoporosis has garnered significant attention. Most studies examining the association ...

A cross-sectional and bioinformatics-based analysis: perirenal fat thickness as a superior predictor of kidney stone disease.

Lipids in health and disease
BACKGROUND: Kidney stone disease (KSD) is a growing global health concern, with obesity (OB) as a major risk factor linked to metabolic dysfunction and chronic inflammation. Although the common method for evaluating OB is body mass index (BMI), it is...

Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis.

Scientific reports
The accurate classification of obesity is essential for public health and clinical decision-making. Traditional anthropometric measures such as body mass index (BMI) have limitations in differentiating between fat and lean mass. This study aimed to e...