AI Medical Compendium Topic

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Voting

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Can biased search results change people's opinions about anything at all? a close replication of the Search Engine Manipulation Effect (SEME).

PloS one
In previous experiments we have conducted on the Search Engine Manipulation Effect (SEME), we have focused on the ability of biased search results to shift voting preferences. In three new experiments with a total of 1,137 US residents (mean age = 33...

An Implicit-Explicit Prototypical Alignment Framework for Semi-Supervised Medical Image Segmentation.

IEEE journal of biomedical and health informatics
Semi-supervised learning methods have been explored to mitigate the scarcity of pixel-level annotation in medical image segmentation tasks. Consistency learning, serving as a mainstream method in semi-supervised training, suffers from low efficiency ...

Artificial intelligence in tongue diagnosis: classification of tongue lesions and normal tongue images using deep convolutional neural network.

BMC medical imaging
OBJECTIVE: This study aims to classify tongue lesion types using tongue images utilizing Deep Convolutional Neural Networks (DCNNs).

Enhanced Binary Classification of Gait Disorders Using a Machine Learning Majority Voting Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study introduces a machine learning-based methodology for classifying healthy individuals and those with gait disorders, employing a merged data set from 'GaitRec' and 'Gutenberg.' Key gait features were extracted from the normalized ground reac...

MultiFeatVotPIP: a voting-based ensemble learning framework for predicting proinflammatory peptides.

Briefings in bioinformatics
Inflammatory responses may lead to tissue or organ damage, and proinflammatory peptides (PIPs) are signaling peptides that can induce such responses. Many diseases have been redefined as inflammatory diseases. To identify PIPs more efficiently, we ex...

Late feature fusion using neural network with voting classifier for Parkinson's disease detection.

BMC medical informatics and decision making
Parkinson's disease (PD) is classified as a neurological, progressive illness brought on by cell death in the posterior midbrain. Early PD detection will assist doctors in reducing the disease's consequences. A collection of skilled models that may b...

Multi-loss, feature fusion and improved top-two-voting ensemble for facial expression recognition in the wild.

Neural networks : the official journal of the International Neural Network Society
Facial expression recognition (FER) in the wild is a challenging pattern recognition task affected by the images' low quality and has attracted broad interest in computer vision. Existing FER methods failed to obtain sufficient accuracy to support th...

Enhancing stroke disease classification through machine learning models via a novel voting system by feature selection techniques.

PloS one
Heart disease remains a leading cause of mortality and morbidity worldwide, necessitating the development of accurate and reliable predictive models to facilitate early detection and intervention. While state of the art work has focused on various ma...

Zero-shot 3D anomaly detection via online voter mechanism.

Neural networks : the official journal of the International Neural Network Society
3D anomaly detection aims to solve the problem that image anomaly detection is greatly affected by lighting conditions. As commercial confidentiality and personal privacy become increasingly paramount, access to training samples is often restricted. ...

A robust ensemble framework for anticancer peptide classification using multi-model voting approach.

Computers in biology and medicine
Anticancer peptides (ACPs) hold great potential for cancer therapeutics, yet accurately identifying them remains a challenging task due to the complexity of peptide sequences and their interactions with biological systems. In this study, we propose a...