AIMC Topic: Humans

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Automated mold defects classification in paintings: A comparison of machine learning and rule-based techniques.

PloS one
Mold defects pose a significant risk to the preservation of valuable fine art paintings, typically arising from fungal growth in humid environments. This paper presents a novel approach for detecting and categorizing mold defects in fine art painting...

AI-assisted radiologists vs. standard double reading for rib fracture detection on CT images: A real-world clinical study.

PloS one
To evaluate the diagnostic accuracy of artificial intelligence (AI) assisted radiologists and standard double-reading in real-world clinical settings for rib fractures (RFs) detection on CT images. This study included 243 consecutive chest trauma pat...

Combating trade in illegal wood and forest products with machine learning.

PloS one
Trade in wood and forest products spans the global supply chain. Illegal logging and associated trade in forest products present a persistent threat to vulnerable ecosystems and communities. Illegal timber trade has been linked to violations of tax a...

Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms.

PloS one
BACKGROUND: Stunting is a vital indicator of chronic undernutrition that reveals a failure to reach linear growth. Investigating growth and nutrition status during adolescence, in addition to infancy and childhood is very crucial. However, the availa...

Generative adversarial local density-based unsupervised anomaly detection.

PloS one
Anomaly detection is crucial in areas such as financial fraud identification, cybersecurity defense, and health monitoring, as it directly affects the accuracy and security of decision-making. Existing generative adversarial nets (GANs)-based anomaly...

Pedestrian POSE estimation using multi-branched deep learning pose net.

PloS one
In human activity-recognition scenarios, including head and entire body pose and orientations, recognizing the pose and direction of a pedestrian is considered a complex problem. A person may be traveling in one sideway while focusing his attention o...

Machine learning model to predict the adherence of tuberculosis patients experiencing increased levels of liver enzymes in Indonesia.

PloS one
Indonesia is still the second-highest tuberculosis burden country in the world. The antituberculosis adverse drug reaction and adherence may influence the success of treatment. The objective of this study is to define the model for predicting the adh...

Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal.

PloS one
This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using only self-reported survey data. Such a model could enable scalable and cost-effective screening and ta...

Exploiting the similarity of dissimilarities for biomedical applications and enhanced machine learning.

PLoS computational biology
The "similarity of dissimilarities" is an emerging paradigm in biomedical science with significant implications for protein function prediction, machine learning (ML), and personalized medicine. In protein function prediction, recognizing dissimilari...

Unveiling diabetes onset: Optimized XGBoost with Bayesian optimization for enhanced prediction.

PloS one
Diabetes, a chronic condition affecting millions worldwide, necessitates early intervention to prevent severe complications. While accurately predicting diabetes onset or progression remains challenging due to complex and imbalanced datasets, recent ...