AIMC Topic: Bayes Theorem

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A Tri-Stage Wrapper-Filter Feature Selection Framework for Disease Classification.

Sensors (Basel, Switzerland)
In machine learning and data science, feature selection is considered as a crucial step of data preprocessing. When we directly apply the raw data for classification or clustering purposes, sometimes we observe that the learning algorithms do not per...

Machine-learning model selection and parameter estimation from kinetic data of complex first-order reaction systems.

PloS one
Dealing with a system of first-order reactions is a recurrent issue in chemometrics, especially in the analysis of data obtained by spectroscopic methods applied on complex biological systems. We argue that global multiexponential fitting, the still ...

The effect of principal component analysis in the diagnosis of congestive heart failure via heart rate variability analysis.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
In this study, we investigated the effect of principal component analysis (PCA) in congestive heart failure (CHF) diagnosis using various machine learning algorithms from 5-min HRV data. The extracted 59 heart rate variability (HRV) features consist ...

Early pregnancy diagnosis of rabbits: A non-invasive approach using Vis-NIR spatially resolved spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Pregnancy diagnosis is essential for rabbit's reproductive management. The early identification of non-pregnant rabbits allows for earlier re-insemination, increases the service rate, and reduces the laboring interval in commercial operations. The ob...

Rapid Reconstruction of Time-varying Gene Regulatory Networks with Limited Main Memory.

IEEE/ACM transactions on computational biology and bioinformatics
Reconstruction of time-varying gene regulatory networks underlying a time-series gene expression data is a fundamental challenge in the computational systems biology. The challenge increases multi-fold if the target networks need to be constructed fo...

Application of an extreme learning machine network with particle swarm optimization in syndrome classification of primary liver cancer.

Journal of integrative medicine
OBJECTIVE: By optimizing the extreme learning machine network with particle swarm optimization, we established a syndrome classification and prediction model for primary liver cancer (PLC), classified and predicted the syndrome diagnosis of medical r...

The Algorithm of a Game-Based System in the Relation between an Operator and a Technical Object in Management of E-Commerce Logistics Processes with the Use of Machine Learning.

Sensors (Basel, Switzerland)
Machine learning (ML) is applied in various logistic processes utilizing innovative techniques (e.g., the use of drones for automated delivery in e-commerce). Early challenges showed the insufficient drones' steering capacity and cognitive gap relate...

A novel artificial intelligence-based approach for identification of deoxynucleotide aptamers.

PLoS computational biology
The selection of a DNA aptamer through the Systematic Evolution of Ligands by EXponential enrichment (SELEX) method involves multiple binding steps, in which a target and a library of randomized DNA sequences are mixed for selection of a single, nucl...

A credit risk assessment model of borrowers in P2P lending based on BP neural network.

PloS one
Peer-to-Peer (P2P) lending provides convenient and efficient financing channels for small and medium-sized enterprises and individuals, and therefore it has developed rapidly since entering the market. However, due to the imperfection of the credit s...

Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network.

PloS one
Human errors are considered to be the main causation factors of high-temperature molten metal accidents in metallurgical enterprises. The complex working environment of high- temperature molten metal in metallurgical enterprises has an important infl...