Genetics

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

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Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.

The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric e...

Detecting outliers in case-control cohorts for improving deep learning networks on Schizophrenia prediction.

This study delves into the intricate genetic and clinical aspects of Schizophrenia, a complex mental...

An assessment of the value of deep neural networks in genetic risk prediction for surgically relevant outcomes.

INTRODUCTION: Postoperative complications affect up to 15% of surgical patients constituting a major...

Improving the performance of mutation-based evolving artificial neural networks with self-adaptive mutations.

Neuroevolution is a promising approach for designing artificial neural networks using an evolutionar...

Uncovering substrate specificity determinants of class IIb aminoacyl-tRNA synthetases with machine learning.

Specific amino acid (AA) binding by aminoacyl-tRNA synthetases (aaRSs) is necessary for correct tran...

Seizure Detection of EEG Signals Based on Multi-Channel Long- and Short-Term Memory-Like Spiking Neural Model.

Seizure is a common neurological disorder that usually manifests itself in recurring seizure, and th...

Self-supervised learning for characterising histomorphological diversity and spatial RNA expression prediction across 23 human tissue types.

As vast histological archives are digitised, there is a pressing need to be able to associate specif...

Redefining a new frontier in alkaptonuria therapy with AI-driven drug candidate design via innovation.

A rare metabolic condition called alkaptonuria (AKU) is caused by a decrease in homogentisate 1,2 di...

Hierarchical multi-task deep learning-assisted construction of human gut microbiota reactive oxygen species-scavenging enzymes database.

In the process of oxygen reduction, reactive oxygen species (ROS) are generated as intermediates, in...

Prediction of inherited metabolic disorders using tandem mass spectrometry data with the help of artificial neural networks.

BACKGROUND/AIM: Tandem mass spectrometry is helpful in diagnosing amino acid metabolism disorders, o...

Role of artificial intelligence applied to ultrasound in gynecology oncology: A systematic review.

The aim of this paper was to explore the role of artificial intelligence (AI) applied to ultrasound ...

INDELpred: Improving the prediction and interpretation of indel pathogenicity within the clinical genome.

Small insertions and deletions (indels) are critical yet challenging genetic variations with signifi...

Habitat radiomics and deep learning fusion nomogram to predict EGFR mutation status in stage I non-small cell lung cancer: a multicenter study.

Develop a radiomics nomogram that integrates deep learning, radiomics, and clinical variables to pre...

T-distributed Stochastic Neighbor Network for unsupervised representation learning.

Unsupervised representation learning (URL) is still lack of a reasonable operator (e.g. convolution ...

Applications of spatial transcriptomics and artificial intelligence to develop integrated management of pancreatic cancer.

Cancer is a complex disease intrinsically associated with cellular processes and gene expression. Wi...

Analyzing intelligent tourism development and public services based on a fuzzy genetic hybrid system to promote environmental and cultural values.

Environmental, cultural, and public service-dependent factors encourage the development of a country...

PreDBP-PLMs: Prediction of DNA-binding proteins based on pre-trained protein language models and convolutional neural networks.

The recognition of DNA-binding proteins (DBPs) is the crucial step to understanding their roles in v...

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