AIMC Topic: Machine Learning

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Automated Detection of Pediatric Foreign Body Aspiration from Chest X-rays Using Machine Learning.

The Laryngoscope
OBJECTIVE/HYPOTHESIS: Standard chest radiographs are a poor diagnostic tool for pediatric foreign body aspiration. Machine learning may improve upon the diagnostic capabilities of chest radiographs. The objective is to develop a machine learning algo...

Prediction of pregnancy-related complications in women undergoing assisted reproduction, using machine learning methods.

Fertility and sterility
OBJECTIVE: To use machine learning methods to develop prediction models of pregnancy complications in women who conceived with assisted reproductive techniques (ART).

Application of machine learning techniques in population pharmacokinetics/pharmacodynamics modeling.

Drug metabolism and pharmacokinetics
Population pharmacokinetics/pharmacodynamics (pop-PK/PD) consolidates pharmacokinetic and pharmacodynamic data from many subjects to understand inter- and intra-individual variability due to patient backgrounds, including disease state and genetics. ...

Classification of self-limited epilepsy with centrotemporal spikes by classical machine learning and deep learning based on electroencephalogram data.

Brain research
Electroencephalogram (EEG) has been widely utilized as a valuable assessment tool for diagnosing epilepsy in hospital settings. However, clinical diagnosis of patients with self-limited epilepsy with centrotemporal spikes (SeLECTS) is challenging due...

Machine learning prediction of footwear slip resistance on glycerol-contaminated surfaces: A pilot study.

Applied ergonomics
Slippery surfaces due to oil spills pose a significant risk in various environments, including industrial workplaces, kitchens, garages, and outdoor areas. These situations can lead to accidents and falls, resulting in injuries that range from minor ...

Accuracy of automated segmentation and volumetry of acute intracerebral hemorrhage following minimally invasive surgery using a patch-based convolutional neural network in a small dataset.

Neuroradiology
PURPOSE: In cases of acute intracerebral hemorrhage (ICH) volume estimation is of prognostic and therapeutic value following minimally invasive surgery (MIS). The ABC/2 method is widely used, but suffers from inaccuracies and is time consuming. Super...

Tree-structured parzen estimator optimized-automated machine learning assisted by meta-analysis for predicting biochar-driven NO mitigation effect in constructed wetlands.

Journal of environmental management
Biochar is a carbon-neutral tool for combating climate change. Artificial intelligence applications to estimate the biochar mitigation effect on greenhouse gases (GHGs) can assist scientists in making more informed solutions. However, there is also e...

Application of the performance of machine learning techniques as support in the prediction of school dropout.

Scientific reports
This article presents a study, intending to design a model with 90% reliability, which helps in the prediction of school dropouts in higher and secondary education institutions, implementing machine learning techniques. The collection of information ...

The insightful water quality analysis and predictive model establishment via machine learning in dual-source drinking water distribution system.

Environmental research
Dual-source drinking water distribution systems (DWDS) over single-source water supply systems are becoming more practical in providing water for megacities. However, the more complex water supply problems are also generated, especially at the hydrau...