AIMC Topic: Body Weight

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Artificial intelligence-driven anthropometric assessment for young children: evaluating the accuracy and practicality of a digital image-based length and weight prediction tool.

BMJ health & care informatics
BACKGROUND: Monitoring early childhood growth is vital, as growth faltering could indicate nutritional or health issues requiring prompt intervention. Our study's aim was to assess the performance of a length-weight artificial intelligence (LWAI) too...

End-to-end deep SAE-DNN model for predicting Egyptian buffalo calf sex, weight, and daily milk yield.

Tropical animal health and production
In the present study, a novel stacked Sparse Autoencoder-Deep Neural Network (SAE-DNN) learning prediction model was applied to predict calf sex, weight, and daily milk yield for dairy buffalo. First, SAE stage extracts the unique statistical feature...

CattleNet-XAI: An explainable CNN framework for efficient cattle weight estimation.

PloS one
Accurate estimation of cattle weight is essential for effective farm management, health assessment, and productivity optimization. Traditional manual methods for weight estimation, however, are labor-intensive, time-consuming, and prone to inaccuraci...

SHAP-enhanced machine learning identifies modifiable obesity predictors across adolescent weight groups: A 2021 YRBSS analysis.

PloS one
BACKGROUND: The growing prevalence of obesity in adolescents around the world poses a major threat to public health. This research uses machine learning models to examine the main causes of obesity, in contrast to standard information that typically ...

The application and predictive value of the weight-adjusted-waist index in BC prevalence assessment: a comprehensive statistical and machine learning analysis using NHANES data.

BMC cancer
BACKGROUND: Obesity is a known risk factor for breast cancer (BC), but conventional metrics such as body mass index (BMI) may insufficiently capture central adiposity. The weight-adjusted waist index (WWI) has emerged as a potentially superior anthro...

A Novel Dual-Network Approach for Real-Time Liveweight Estimation in Precision Livestock Management.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The increasing demand for automation in livestock farming scenarios highlights the need for effective noncontact measurement methods. The current methods typically require either fixed postures and specific positions of the target animals or high com...

On-farm 3D images of beef cattle for the prediction of carcass classification traits and cold carcass weight.

Animal : an international journal of animal bioscience
For beef cattle, subjective methods tend to be used on-farm for assessing readiness for slaughter. This means that the target classification grades cannot be accurately estimated, leading to over- and under-finished animals being sent to slaughter. T...

Obesity classification: a comparative study of machine learning models excluding weight and height data.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity classification.

Artificial intelligence for weight estimation in paediatric emergency care.

BMJ paediatrics open
OBJECTIVE: To develop and validate a paediatric weight estimation model adapted to the characteristics of the Spanish population as an alternative to currently extended methods.

Conventional and machine learning-based analysis of age, body weight and body height significance in knot position-related thyrohyoid and cervical spine fractures in suicidal hangings.

International journal of legal medicine
The thyrohyoid complex and cervical spine fracture distribution patterns may reflect the knot position as the force distribution by the noose to different neck regions may vary depending on it. Recently, machine learning models (MLm) were used to cla...