Genetics

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

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Showing 1429-1449 of 10,366 articles
Machine learning algorithms translate big data into predictive breeding accuracy.

Statistical machine learning (ML) extracts patterns from extensive genomic, phenotypic, and environm...

AI-Based solutions for current challenges in regenerative medicine.

The emergence of Artificial Intelligence (AI) and its usage in regenerative medicine represents a si...

Harnessing explainable artificial intelligence for patient-to-clinical-trial matching: A proof-of-concept pilot study using phase I oncology trials.

This study aims to develop explainable AI methods for matching patients with phase 1 oncology clinic...

The role of artificial intelligence in the management of liver diseases.

Universal neonatal hepatitis B virus (HBV) vaccination and the advent of direct-acting antivirals (D...

Predicting laboratory aspirin resistance in Chinese stroke patients using machine learning models by GP1BA polymorphism.

This study aims to use machine learning model to predict laboratory aspirin resistance (AR) in Chine...

Searching Discriminative Regions for Convolutional Neural Networks in Fundus Image Classification With Genetic Algorithms.

Deep convolutional neural networks (CNNs) have been widely used for fundus image classification and ...

Machine learning identification of NK cell immune characteristics in hepatocellular carcinoma based on single-cell sequencing and bulk RNA sequencing.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly malignant tumor; however, its immune microenv...

Applying machine learning and genetic algorithms accelerated for optimizing ethanol production.

Corn straws can produce bioethanol via simultaneous saccharification and co-fermentation (SSCF). How...

Enhancing Data Science and Genomics Capacity of a Historically Black Medical College Through Interdisciplinary Training and Research Collaborations.

As data grows exponentially across diverse fields, effectively leveraging big data has become increa...

TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs.

Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-M...

Identification of novel biomarkers for atherosclerosis using single-cell RNA sequencing and machine learning.

Atherosclerosis (AS) is a predominant etiological factor in numerous cardiovascular diseases, with i...

A genetic programming Rician noise reduction and explainable deep learning model for Alzheimer's diseases severity prediction.

BACKGROUND: Degradation of magnetic resonance imaging (MRI) remains a challenging issue, with noise ...

Graph based recurrent network for context specific synthetic lethality prediction.

The concept of synthetic lethality (SL) has been successfully used for targeted therapies. To furthe...

Integrative multi-omic and machine learning approach for prognostic stratification and therapeutic targeting in lung squamous cell carcinoma.

The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to th...

Triple and quadruple optimization for feature selection in cancer biomarker discovery.

The proliferation of omics data has advanced cancer biomarker discovery but often falls short in ext...

Machine learning-aided microRNA discovery for olive oil quality.

MicroRNAs (miRNAs) are key regulators of gene expression in plants, influencing various biological p...

Comparative study of machine learning approaches integrated with genetic algorithm for IVF success prediction.

INTRODUCTION: IVF is a widely-used assisted reproductive technology with a consistent success rate o...

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