AIMC Topic: Algorithms

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Harnessing machine learning for EEG signal analysis: Innovations in depth of anaesthesia assessment.

Artificial intelligence in medicine
Anaesthesia, crucial to surgical practice, is undergoing renewed scrutiny due to the integration of artificial intelligence in its medical use. The precise control over the temporary loss of consciousness is vital to ensure safe, pain-free procedures...

Automated detection of small bowel lesions based on capsule endoscopy using deep learning algorithm.

Clinics and research in hepatology and gastroenterology
BACKGROUND: In order to overcome the challenges of lesion detection in capsule endoscopy (CE), we improved the YOLOv5-based deep learning algorithm and established the CE-YOLOv5 algorithm to identify small bowel lesions captured by CE.

Machine learning for high solid anaerobic digestion: Performance prediction and optimization.

Bioresource technology
Biogas production through anaerobic digestion (AD) is one of the complex non-linear biological processes, wherein understanding its dynamics plays a crucial role towards process control and optimization. In this work, a machine learning based biogas ...

Enhancing urban blue-green landscape quality assessment through hybrid genetic algorithm-back propagation (GA-BP) neural network approach: a case study in Fucheng, China.

Environmental monitoring and assessment
This study employs an artificial neural network optimization algorithm, enhanced with a Genetic Algorithm-Back Propagation (GA-BP) network, to assess the service quality of urban water bodies and green spaces, aiming to promote healthy urban environm...

Bio-QSARs 2.0: Unlocking a new level of predictive power for machine learning-based ecotoxicity predictions by exploiting chemical and biological information.

Environment international
Practical, legal, and ethical reasons necessitate the development of methods to replace animal experiments. Computational techniques to acquire information that traditionally relied on animal testing are considered a crucial pillar among these so-cal...

DBDNMF: A Dual Branch Deep Neural Matrix Factorization method for drug response prediction.

PLoS computational biology
Anti-cancer response of cell lines to drugs is in urgent need for individualized precision medical decision-making in the era of precision medicine. Measurements with wet-experiments is time-consuming and expensive and it is almost impossible for wid...

Evaluation of water resources security in Anhui Province based on GA-BP model.

Environmental science and pollution research international
Water resources security is an important cornerstone of regional sustainable development, but the current evaluation system of water resources security is not scientific, and the measurement of safety level has not been optimized by combining algorit...

Manifold Learning-Based Common Spatial Pattern for EEG Signal Classification.

IEEE journal of biomedical and health informatics
EEG signal classification using Riemannian manifolds has shown great potential. However, the huge computational cost associated with Riemannian metrics poses challenges for applying Riemannian methods, particularly in high-dimensional feature data. T...

Graph Representation Learning for Large-Scale Neuronal Morphological Analysis.

IEEE transactions on neural networks and learning systems
The analysis of neuronal morphological data is essential to investigate the neuronal properties and brain mechanisms. The complex morphologies, absence of annotations, and sheer volume of these data pose significant challenges in neuronal morphologic...

Machine Learning Approach to Study Social Determinants of Chronic Illness in India: A Comparative Analysis.

Indian journal of public health
BACKGROUND: Several studies on noncommunicable diseases (NCDs) have been carried out worldwide, the basis of most of which is the identification of risk factors-modifiable (or behavioral) and metabolic. Majority of the NCDs are due to sociodemographi...