Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Discriminating Neoplastic from Nonneoplastic Tissues Using an miRNA-Based Deep Cancer Classifier.

Next-generation sequencing has enabled the collection of large biological data sets, allowing novel ...

Learning the local landscape of protein structures with convolutional neural networks.

One fundamental problem of protein biochemistry is to predict protein structure from amino acid sequ...

A robust and stable gene selection algorithm based on graph theory and machine learning.

BACKGROUND: Nowadays we are observing an explosion of gene expression data with phenotypes. It enabl...

Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images.

Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along w...

Deep Learning of the Retina Enables Phenome- and Genome-Wide Analyses of the Microvasculature.

BACKGROUND: The microvasculature, the smallest blood vessels in the body, has key roles in maintenan...

Machine learning random forest for predicting oncosomatic variant NGS analysis.

Since 2017, we have used IonTorrent NGS platform in our hospital to diagnose and treat cancer. Analy...

Development of a Machine Learning Classifier for Brain Tumors Diagnosis Based on DNA Methylation Profile.

More than 150 types of brain tumors have been documented. Accurate diagnosis is important for makin...

Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

PURPOSE: This study aimed to explore the predictive ability of deep learning (DL) for the common epi...

FTWSVM-SR: DNA-Binding Proteins Identification via Fuzzy Twin Support Vector Machines on Self-Representation.

Due to the high cost of DNA-binding proteins (DBPs) detection, many machine learning algorithms (ML)...

Establishment of a 13 genes-based molecular prediction score model to discriminate the neurotoxic potential of food relevant-chemicals.

Although many neurotoxicity prediction studies of food additives have been developed, they are appli...

Accuracy of deep learning-based computed tomography diagnostic system for COVID-19: A consecutive sampling external validation cohort study.

Ali-M3, an artificial intelligence program, analyzes chest computed tomography (CT) and detects the ...

Combining genetic risk score with artificial neural network to predict the efficacy of folic acid therapy to hyperhomocysteinemia.

Artificial neural network (ANN) is the main tool to dig data and was inspired by the human brain and...

Correspondence between neuroevolution and gradient descent.

We show analytically that training a neural network by conditioned stochastic mutation or neuroevolu...

PrognosiT: Pathway/gene set-based tumour volume prediction using multiple kernel learning.

BACKGROUND: Identification of molecular mechanisms that determine tumour progression in cancer patie...

A Feature Fusion Predictor for RNA Pseudouridine Sites with Particle Swarm Optimizer Based Feature Selection and Ensemble Learning Approach.

RNA pseudouridine modification is particularly important in a variety of cellular biological and phy...

ColGen: An end-to-end deep learning model to predict thermal stability of de novo collagen sequences.

Collagen is the most abundant structural protein in humans, with dozens of sequence variants account...

Deep Learning and Pathomics Analyses Reveal Cell Nuclei as Important Features for Mutation Prediction of BRAF-Mutated Melanomas.

Image-based analysis as a method for mutation detection can be advantageous in settings when tumor t...

Prediction of genetic alteration of phospholipase C isozymes in brain disorders: Studies with deep learning.

Genetic mutations leading to the development of various diseases, such as cancer, diabetes, and neur...

Predicting physiological aging rates from a range of quantitative traits using machine learning.

It is widely thought that individuals age at different rates. A method that measures "physiological ...

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