AIMC Topic: Algorithms

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Advancing prostate cancer detection: a comparative analysis of PCLDA-SVM and PCLDA-KNN classifiers for enhanced diagnostic accuracy.

Scientific reports
This investigation aimed to assess the effectiveness of different classification models in diagnosing prostate cancer using a screening dataset obtained from the National Cancer Institute's Cancer Data Access System. The dataset was first reduced usi...

Spatial differentiation of carbon emissions from energy consumption based on machine learning algorithm: A case study during 2015-2020 in Shaanxi, China.

Journal of environmental sciences (China)
Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide. Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem. Previous studies relied on s...

An unsupervised wavelet neural network model for approximating the solutions of non-linear nervous stomach model governed by tension, food and medicine.

Computer methods in biomechanics and biomedical engineering
The human stomach is a complex organ. Its role is to degrade food particles by using mechanical forces and chemical reactions in order to release nutrients. All ingested items, including our nutrition, should first pass through the stomach, making it...

A bi-layer model for identification of piwiRNA using deep neural learning.

Journal of biomolecular structure & dynamics
piwiRNA is a kind of non-coding RNA (ncRNA) that cannot be translated into proteins. It helps in understanding the study of gametes generation and regulation of gene expression over both transcriptional and post-transcriptional levels. piwiRNA has th...

Layer adaptive node selection in Bayesian neural networks: Statistical guarantees and implementation details.

Neural networks : the official journal of the International Neural Network Society
Sparse deep neural networks have proven to be efficient for predictive model building in large-scale studies. Although several works have studied theoretical and numerical properties of sparse neural architectures, they have primarily focused on the ...

Automated Age-Related Macular Degeneration Detector on Optical Coherence Tomography Images Using Slice-Sum Local Binary Patterns and Support Vector Machine.

Sensors (Basel, Switzerland)
Artificial intelligence has revolutionised smart medicine, resulting in enhanced medical care. This study presents an automated detector chip for age-related macular degeneration (AMD) using a support vector machine (SVM) and three-dimensional (3D) o...

Neuromorphic applications in medicine.

Journal of neural engineering
In recent years, there has been a growing demand for miniaturization, low power consumption, quick treatments, and non-invasive clinical strategies in the healthcare industry. To meet these demands, healthcare professionals are seeking new technologi...

Reference standard for the evaluation of automatic segmentation algorithms: Quantification of inter observer variability of manual delineation of prostate contour on MRI.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to investigate the relationship between inter-reader variability in manual prostate contour segmentation on magnetic resonance imaging (MRI) examinations and determine the optimal number of readers required to e...

Quantum Machine Learning Predicting ADME-Tox Properties in Drug Discovery.

Journal of chemical information and modeling
In the drug discovery paradigm, the evaluation of absorption, distribution, metabolism, and excretion (ADME) and toxicity properties of new chemical entities is one of the most critical issues, which is a time-consuming process, immensely expensive, ...

A multilayered bidirectional associative memory model for learning nonlinear tasks.

Neural networks : the official journal of the International Neural Network Society
A multilayered bidirectional associative memory neural network is proposed to account for learning nonlinear types of association. The model (denoted as the MF-BAM) is composed of two modules, the Multi-Feature extracting bidirectional associative me...