AIMC Topic: Machine Learning

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Liver Fat Fraction and Machine Learning Improve Steatohepatitis Diagnosis in Liver Transplant Patients.

NMR in biomedicine
Machine learning identifies liver fat fraction (FF) measured by H MR spectroscopy, insulinemia, and elastography as robust, non-invasive biomarkers for diagnosing steatohepatitis in liver transplant patients, validated through decision tree analysis....

Clinical Decision Support for Septic Shock in the Emergency Department: A Cluster Randomized Trial.

Pediatrics
BACKGROUND AND OBJECTIVES: Delays in septic shock diagnosis cause preventable mortality in children. Evidence is limited around early recognition strategies. The hypothesis was that clinical decision support (CDS) based on machine-learning predictive...

Using machine learning to unravel chemical and meteorological effects on ground-level ozone: Insights for ozone-climate control strategies.

Environment international
In the context of climate change, various countries/regions across East Asia have witnessed severe ground-level ozone (O) pollution, which poses potential health risks to the public. The complex relationships between O and its drivers, including the ...

Modeling and prediction of climate change impacts on water resources vulnerability: A multi-model approach.

Journal of environmental management
In a rapidly changing world, uncontrolled climate change worsens water scarcity disrupting hydrological cycles and hindering sustainable development. Addressing water resources vulnerability requires holistic approaches to better understand complex s...

Optimizing swine manure composting parameters with integrated CatBoost and XGBoost models: nitrogen loss mitigation and mechanism.

Journal of environmental management
In this study, machine learning was used to optimize the aerobic composting process of swine manure to enhance nitrogen retention and compost maturity in order to meet the demand for high-quality organic fertilizers in sustainable agriculture. In thi...

Short-term spatial prediction of algal blooms in Lake Taihu via machine learning and GOCI observations.

Journal of environmental management
Harmful algal blooms are critical issues in eutrophic lakes worldwide. However, predicting the spatial distribution of algal blooms at the pixel level is still a challenge. In this study, floating algae cover (FAC) was used to extract algal coverage ...

Automated 3D facial smile attractiveness assessment before and after orthognathic surgery using transfer learning: A preliminary study.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
The aesthetic appearance of the mouth during smiling significantly influences facial attractiveness, thereby, making smile analysis crucial in orthodontics, craniofacial surgery, and cosmetic dentistry. Accurate and quantitative evaluation of facial ...

Exploring best-performing radiomic features with combined multilevel discrete wavelet decompositions for multiclass COVID-19 classification using chest X-ray images.

Computers in biology and medicine
Discrete wavelet transforms have been applied in many machine learning models for the analysis of COVID-19; however, little is known about the impact of combined multilevel wavelet decompositions for the disease identification. This study proposes a ...

Body Weight Estimation in Holstein × Zebu Crossbred Heifers: Comparative Analysis of XGBoost and LightGBM Algorithms.

Veterinary medicine and science
This study evaluates the effectiveness of XGBoost and LightGBM algorithms for estimating the live weight of Holstein×Zebu crossbred heifers. The study compares the performance of both algorithms using a wide range of biometric measurements and tests ...

Computational modelling of olfactory receptors.

Biochimica et biophysica acta. General subjects
Olfactory receptors (ORs), the largest subfamily of G protein-coupled receptors, are essential for detecting and interpreting environmental odorants in animals. Understanding their function is crucial for deciphering olfactory perception and explorin...