AIMC Topic: Entropy

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Entropy-based risk network identification in adolescent self-injurious behavior using machine learning and network analysis.

Translational psychiatry
Adolescent Self-Injurious Behavior (SIB) is a significant global public health issue, with a lifetime prevalence rate of approximately 13.7%. As awareness of SIB rises, there is an urgent need for effective prediction mechanisms to enable early ident...

Advanced dynamic ensemble framework with explainability driven insights for precision brain tumor classification across datasets.

Scientific reports
Accurate detection of brain tumors remains a significant challenge due to the diversity of tumor types along with human interventions during diagnostic process. This study proposes a novel ensemble deep learning system for accurate brain tumor classi...

Transfer learning based deep architecture for lung cancer classification using CT image with pattern and entropy based feature set.

Scientific reports
Early detection of lung cancer, which remains one of the leading causes of death worldwide, is important for improved prognosis, and CT scanning is an important diagnostic modality. Lung cancer classification according to CT scan is challenging since...

Estimating the spatial distribution and exploring the factors influencing cultivated land quality through a hybrid random forest and Bayesian maximum entropy model.

Environmental research
Cultivated land is one of the most valuable agricultural resources; its quality is not only the foundation of national food security but also a crucial issue for global sustainable development. However, owing to data limitations and spatial heterogen...

EEG quantization and entropy of multi-step transition probabilities for driver drowsiness detection via LSTM.

Computers in biology and medicine
Detecting driver drowsiness through electroencephalogram (EEG) poses challenges due to the complexity and variability of brain activity across different subjects. This study proposes a feature extraction pipeline combined with a Long Short-Term Memor...

Exploring entropy measures with topological indices on colorectal cancer drugs using curvilinear regression analysis and machine learning approaches.

PloS one
A topological index is a numerical value derived from the structure of a molecule or graph that provides useful information about the molecule's physical, chemical, or biological properties. These indices are especially important in chemo-informatics...

A Bayesian Maximum Entropy Fusion model for enhanced prediction and risk assessment of fluoride and arsenic contamination in groundwater.

Journal of contaminant hydrology
In the central and western regions of Jilin Province, excessive groundwater extraction has resulted in elevated levels of fluoride (F) and arsenic (As) in drinking water. Prolonged exposure to these contaminants is linked to endemic health issues, in...

Linear and nonlinear features of EEG microstate associated with insomnia.

Sleep medicine
BACKGROUND: Numerous studies have revealed abnormalities in EEG microstate in insomnia, primarily quantified using linear features, whereas nonlinear metrics remain underexplored. This study aimed to compare linear and nonlinear features and further ...

Entropy-driven deep learning framework for epilepsy detection using electro encephalogram signals.

Neuroscience
Epilepsy is one of the most frequently occurring neurological disorders that require early and accurate detection. This paper introduces a novel approach for the automatic identification of epilepsy in EEG signals by incorporating advanced entropy-ba...

A spectral filtering approach to represent exemplars for visual few-shot classification.

Neural networks : the official journal of the International Neural Network Society
Prototype is widely used to represent internal structure of category for few-shot learning, which was proposed as a simple inductive bias to address the issue of overfitting. However, for categories where prototypes do not exist or are difficult to r...