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Gene Frequency

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Fast and accurate deep learning scans for signatures of natural selection in genomes using FASTER-NN.

Communications biology
Deep learning classification models based on Convolutional Neural Networks (CNNs) are increasingly used in population genetic inference for detecting signatures of natural selection. Prevailing detection methods treat the design of the classifier as ...

Artificial Intelligence-Driven Prediction Revealed CFTR Associated with Therapy Outcome of Breast Cancer: A Feasibility Study.

Oncology
INTRODUCTION: In silico tools capable of predicting the functional consequences of genomic differences between individuals, many of which are AI-driven, have been the most effective over the past two decades for non-synonymous single nucleotide varia...

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

HGG advances
Small insertions and deletions (indels) are critical yet challenging genetic variations with significant clinical implications. However, the identification of pathogenic indels from neutral variants in clinical contexts remains an understudied proble...

Ancestry analysis using a self-developed 56 AIM-InDel loci and machine learning methods.

Forensic science international
Insertion/deletion (InDel) polymorphisms can be used as one of the ancestry-informative markers in ancestry analysis. In this study, a self-developed panel consisting of 56 ancestry-informative InDels was used to investigate the genetic structures an...

AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples.

Experimental & molecular medicine
The detection of somatic DNA variants in tumor samples with low tumor purity or sequencing depth remains a daunting challenge despite numerous attempts to address this problem. In this study, we constructed a substantially extended set of actual posi...

Gene-specific machine learning for pathogenicity prediction of rare BRCA1 and BRCA2 missense variants.

Scientific reports
Machine learning-based pathogenicity prediction helps interpret rare missense variants of BRCA1 and BRCA2, which are associated with hereditary cancers. Recent studies have shown that classifiers trained using variants of a specific gene or a set of ...

Improving variant calling using population data and deep learning.

BMC bioinformatics
Large-scale population variant data is often used to filter and aid interpretation of variant calls in a single sample. These approaches do not incorporate population information directly into the process of variant calling, and are often limited to ...

Retrospective Data Analysis of the Influence of Age and Sex on TPMT Activity and Its Phenotype-Genotype Correlation.

The journal of applied laboratory medicine
BACKGROUND: Therapeutic efficacy and toxicity of thiopurine drugs (used as anticancer and immunosuppressant agents) are affected by thiopurine S-methyltransferase (TPMT) enzyme activity. genotype and/or phenotype is used to predict the risk for adve...

Serum vitamin D deficiency and vitamin D receptor gene polymorphism are associated with increased risk of cardiovascular disease in a Chinese rural population.

Nutrition research (New York, N.Y.)
Several studies have reported a conflicting association between vitamin D deficiency, vitamin D receptor (VDR) polymorphism, and the risk of cardiovascular disease (CVD). We hypothesized that serum 25(OH)D concentrations and single nucleotide polymor...

De novo transcriptome assembly of pummelo and molecular marker development.

PloS one
Pummelo (Citrus grandis) is an important fruit crop worldwide because of its nutritional value. To accelerate the pummelo breeding program, it is essential to obtain extensive genetic information and develop relative molecular markers. Here, we obtai...