AIMC Topic: Bayes Theorem

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A Novel Supervised Filter Feature Selection Method Based on Gaussian Probability Density for Fault Diagnosis of Permanent Magnet DC Motors.

Sensors (Basel, Switzerland)
For permanent magnet DC motors (PMDCMs), the amplitude of the current signals gradually decreases after the motor starts. In this work, the time domain features and time-frequency-domain features extracted from several successive segments of current ...

Implementation of Machine Learning Mechanism for Recognising Prostate Cancer through Photoacoustic Signal.

Contrast media & molecular imaging
Biological tissues may be studied using photoacoustic (PA) spectroscopy, which can yield a wealth of physical and chemical data. However, it is really challenging to directly analyse these tissues because of a lot of data. Data mining techniques can ...

TransMorph: Transformer for unsupervised medical image registration.

Medical image analysis
In the last decade, convolutional neural networks (ConvNets) have been a major focus of research in medical image analysis. However, the performances of ConvNets may be limited by a lack of explicit consideration of the long-range spatial relationshi...

Analysis of Graphic Design Based on AI Interaction Technology.

Journal of environmental and public health
The naive Bayes classification algorithm is used to determine the plane feature vector, and the color image enhancement algorithm based on the visual characteristics is used to improve the local contrast of the plane visual image. In addition, based ...

Investigation of Applying Machine Learning and Hyperparameter Tuned Deep Learning Approaches for Arrhythmia Detection in ECG Images.

Computational and mathematical methods in medicine
The level of patient's illness is determined by diagnosing the problem through different methods like physically examining patients, lab test data, and history of patient and by experience. To treat the patient, proper diagnosis is very much importan...

Investigating Methods for Cognitive Workload Estimation for Assistive Robots.

Sensors (Basel, Switzerland)
Robots interacting with humans in assistive contexts have to be sensitive to human cognitive states to be able to provide help when it is needed and not overburden the human when the human is busy. Yet, it is currently still unclear which sensing mod...

Neural network and Bayesian-based prediction of breeding values in Beetal goat.

Tropical animal health and production
The estimation of breeding values is prime concern for animal breeders in order to achieve desired genetic progress of farm animals. However, current methods for estimating BV involve simultaneous selection of animal model which are computationally i...

Chronic back pain sub-grouped via psychosocial, brain and physical factors using machine learning.

Scientific reports
Chronic back pain (CBP) is heterogenous and identifying sub-groups could improve clinical decision making. Machine learning can build upon prior sub-grouping approaches by using a data-driven approach to overcome clinician subjectivity, however, only...

MCluster-VAEs: An end-to-end variational deep learning-based clustering method for subtype discovery using multi-omics data.

Computers in biology and medicine
The discovery of cancer subtypes based on unsupervised clustering helps in providing a precise diagnosis, guide treatment, and improve patients' prognoses. Instead of single-omics data, multi-omics data can improve the clustering performance because ...

COVID-19 safe campus evaluation for universities by a hybrid interval type-2 fuzzy decision-making model.

Environmental science and pollution research international
The fight against the COVID-19 pandemic, which has affected the whole world in recent years and has had devastating effects on all segments of society, has been one of the most important priorities. The Turkish Standards Institution has determined a ...