AIMC Topic: Algorithms

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Heat Flux Sensing for Machine-Learning-Based Personal Thermal Comfort Modeling.

Sensors (Basel, Switzerland)
In recent years, physiological features have gained more attention in developing models of personal thermal comfort for improved and accurate adaptive operation of Human-In-The-Loop (HITL) Heating, Ventilation, and Air-Conditioning (HVAC) systems. Pu...

A new and effective method for human retina optic disc segmentation with fuzzy clustering method based on active contour model.

Medical & biological engineering & computing
In this paper, a new approach is proposed for localization and segmentation of the optic disc in human retina images. This new approach can find the boundary of the optic disc by an initial fuzzy clustering means algorithm. The proposed approach uses...

An artificial neural network and Random Forest identify glyphosate-impacted brackish communities based on 16S rRNA amplicon MiSeq read counts.

Marine pollution bulletin
Machine learning algorithms can be trained on complex data sets to detect, predict, or model specific aspects. Aim of this study was to train an artificial neural network in comparison to a Random Forest model to detect induced changes in microbial c...

Accelerating cardiovascular model building with convolutional neural networks.

Medical & biological engineering & computing
The objective of this work is to reduce the user effort required for 2D segmentation when building patient-specific cardiovascular models using the SimVascular cardiovascular modeling software package. The proposed method uses a fully convolutional n...

Sex estimation: a comparison of techniques based on binary logistic, probit and cumulative probit regression, linear and quadratic discriminant analysis, neural networks, and naïve Bayes classification using ordinal variables.

International journal of legal medicine
The performance of seven classification methods, binary logistic (BLR), probit (PR) and cumulative probit (CPR) regression, linear (LDA) and quadratic (QDA) discriminant analysis, artificial neural networks (ANN), and naïve Bayes classification (NBC)...

A 3D Spatially Weighted Network for Segmentation of Brain Tissue From MRI.

IEEE transactions on medical imaging
The segmentation of brain tissue in MRI is valuable for extracting brain structure to aid diagnosis, treatment and tracking the progression of different neurologic diseases. Medical image data are volumetric and some neural network models for medical...

Artificial Intelligence in Nephrology: Core Concepts, Clinical Applications, and Perspectives.

American journal of kidney diseases : the official journal of the National Kidney Foundation
Artificial intelligence is playing an increasingly important role in many fields of medicine, assisting physicians in most steps of patient management. In nephrology, artificial intelligence can already be used to improve clinical care, hemodialysis ...

Multiclass heterogeneous domain adaptation via bidirectional ECOC projection.

Neural networks : the official journal of the International Neural Network Society
Heterogeneous domain adaptation aims to exploit the source domain data to train a prediction model for the target domain with different input feature space. Current methods either map the data points from different domains with different feature spac...

Automated estimation of the number of contributors in autosomal short tandem repeat profiles using a machine learning approach.

Forensic science international. Genetics
The number of contributors (NOC) to (complex) autosomal STR profiles cannot be determined with absolute certainty due to complicating factors such as allele sharing and allelic drop-out. The precision of NOC estimations can be improved by increasing ...

Online sequential class-specific extreme learning machine for binary imbalanced learning.

Neural networks : the official journal of the International Neural Network Society
Many real-world applications suffer from the class imbalance problem, in which some classes have significantly fewer examples compared to the other classes. In this paper, we focus on online sequential learning methods, which are considerably more pr...