AIMC Topic: Young Adult

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Evaluation of genotoxic effects in Brazilian agricultural workers exposed to pesticides and cigarette smoke using machine-learning algorithms.

Environmental science and pollution research international
Monitoring exposure to xenobiotics by biomarker analyses, such as a micronucleus assay, is extremely important for the precocious detection and prevention of diseases, such as oral cancer. The aim of this study was to evaluate genotoxic effects in ru...

MRI features predict p53 status in lower-grade gliomas via a machine-learning approach.

NeuroImage. Clinical
BACKGROUND: P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images.

EMG-Based Estimation of Limb Movement Using Deep Learning With Recurrent Convolutional Neural Networks.

Artificial organs
A novel model based on deep learning is proposed to estimate kinematic information for myoelectric control from multi-channel electromyogram (EMG) signals. The neural information of limb movement is embedded in EMG signals that are influenced by all ...

Identification of immune signatures predictive of clinical protection from malaria.

PLoS computational biology
Antibodies are thought to play an essential role in naturally acquired immunity to malaria. Prospective cohort studies have frequently shown how continuous exposure to the malaria parasite Plasmodium falciparum cause an accumulation of specific respo...

A parallel MR imaging method using multilayer perceptron.

Medical physics
PURPOSE: To reconstruct MR images from subsampled data, we propose a fast reconstruction method using the multilayer perceptron (MLP) algorithm.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks.

Computational intelligence and neuroscience
Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. Th...

Towards multilevel mental stress assessment using SVM with ECOC: an EEG approach.

Medical & biological engineering & computing
Mental stress has been identified as one of the major contributing factors that leads to various diseases such as heart attack, depression, and stroke. To avoid this, stress quantification is important for clinical intervention and disease prevention...

High-Risk Breast Lesions: A Machine Learning Model to Predict Pathologic Upgrade and Reduce Unnecessary Surgical Excision.

Radiology
Purpose To develop a machine learning model that allows high-risk breast lesions (HRLs) diagnosed with image-guided needle biopsy that require surgical excision to be distinguished from HRLs that are at low risk for upgrade to cancer at surgery and t...

From provocation to aggression: the neural network.

BMC neuroscience
BACKGROUND: In-vivo observations of neural processes during human aggressive behavior are difficult to obtain, limiting the number of studies in this area. To address this gap, the present study implemented a social reactive aggression paradigm in 29...