AIMC Topic: Anthropometry

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Predicting intra-abdominal hypertension using anthropometric measurements and machine learning.

Scientific reports
Almost one in four critically ill patients suffer from intra-abdominal hypertension (IAH). Currently, the gold standard for measuring intra-abdominal pressure (IAP) is via the bladder. Measurement of IAP is important to identify IAH early and thus im...

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.

Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches.

BMC medical informatics and decision making
BACKGROUND: The aim of this study was to evaluate the potential models to determine the most important anthropometric factors associated with type 2 diabetes mellitus (T2DM).

3D face reconstruction for maxillofacial surgery based on morphable models and neural networks: A preliminary assessment for anthropometry accuracy.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
OBJECTIVES: This study aimed to evaluate the anthropometric accuracy of 3D face reconstruction based on neural networks (3DFRBN) using 2D images, including the assessment of global errors and landmarks, as well as linear and angular measurements.

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.

Subject-specific trunk segmental masses prediction for musculoskeletal models using artificial neural networks.

Medical & biological engineering & computing
Accurate determination of body segment parameters is crucial for studying human movement and joint forces using musculoskeletal (MSK) models. However, existing methods for predicting segment mass have limited generalizability and sensitivity to body ...

A deep learning-based pipeline for developing multi-rib shape generative model with populational percentiles or anthropometrics as predictors.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Rib cross-sectional shapes (characterized by the outer contour and cortical bone thickness) affect the rib mechanical response under impact loading, thereby influence the rib injury pattern and risk. A statistical description of the rib shapes or the...

Machine learning approach to assess the association between anthropometric, metabolic, and nutritional status and semen parameters.

Asian journal of andrology
Many lifestyle factors, such as nutritional imbalance leading to obesity, metabolic disorders, and nutritional deficiency, have been identified as potential risk factors for male infertility. The aim of this study was to evaluate the relationship bet...

Exploratory analysis using machine learning algorithms to predict pinch strength by anthropometric and socio-demographic features.

International journal of occupational safety and ergonomics : JOSE
. This study examines the role of different machine learning (ML) algorithms to determine which socio-demographic factors and hand-forearm anthropometric dimensions can be used to accurately predict hand function. . The cross-sectional study was cond...

Resolving the non-uniformity in the feature space of age estimation: A deep learning model based on feature clusters of panoramic images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Age estimation is important in forensics, and numerous techniques have been investigated to estimate age based on various parts of the body. Among them, dental tissue is considered reliable for estimating age as it is less influenced by external fact...