AIMC Topic: Machine Learning

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Flight and Floral Acoustic Signals for Bee Species Identification.

Neotropical entomology
Animal identification is pivotal for ecological studies, yet automated recognition tools for bee species remain underexplored. Here, we present a machine learning approach using a Random Forest algorithm to identify five bee species representing thre...

A machine learning approach for detection of claustrophobic brain activity in electroencephalography.

Scientific reports
Claustrophobia, a phobia with a specific unreasonable and excessive fear of enclosed spaces, can have a considerable impact on an individual's life. Electroencephalography (EEG) has been a tool with potential for studying neural processes in anxiety ...

Development and validation of a machine learning model integrating BUN/Cr ratio for mortality prediction in critically ill atrial fibrillation patients.

Scientific reports
Atrial fibrillation (AF), the most prevalent critical care arrhythmia, demonstrates substantial mortality associations where renal dysfunction management plays a pivotal therapeutic role. We examined the prognostic capacity of admission blood urea ni...

Machine learning framework for predicting susceptibility to obesity.

Scientific reports
Obesity, currently the fifth leading cause of death worldwide, has seen a significant increase in prevalence over the past four decades. Timely identification of obesity risk facilitates proactive measures against associated factors. In this paper, w...

Machine learning reveals limited predictive value of clinical factors for asthma exacerbations.

Scientific reports
While predictors of asthma exacerbation risk are generally well established, predictors of exacerbation severity remain largely undefined. Identifying robust clinical predictors of exacerbation severity is essential to support tailored management str...

Invasive and non-invasive variables prediction models for cardiovascular disease-specific mortality between machine learning vs. traditional statistics.

Scientific reports
This study examined the predictive performance of cardiovascular disease (CVD)-specific mortality using traditional statistical and machine learning models with non-invasive indicators, and assessed whether adding blood lipid profiles improves predic...

The influence of higher education based on machine learning on subjective well-being.

Scientific reports
As higher education becomes increasingly prevalent and accessible in China, a growing number of residents are afforded the option to pursue advanced studies. Can higher education genuinely enhance residents' subjective well-being? The response to thi...

Optimizing high dimensional data classification with a hybrid AI driven feature selection framework and machine learning schema.

Scientific reports
Feature selection (FS) is critical for datasets with multiple variables and features, as it helps eliminate irrelevant elements, thereby improving classification accuracy. Numerous classification strategies are effective in selecting key features fro...

Detection and classification of brain tumor using a hybrid learning model in CT scan images.

Scientific reports
Accurate diagnosis of brain tumors is critical in understanding the prognosis in terms of the type, growth rate, location, removal strategy, and overall well-being of the patients. Among different modalities used for the detection and classification ...