AIMC Topic: Disease

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DeepCNV: a deep learning approach for authenticating copy number variations.

Briefings in bioinformatics Sep 2, 2021
Copy number variations (CNVs) are an important class of variations contributing to the pathogenesis of many disease phenotypes. Detecting CNVs from genomic data remains difficult, and the most currently applied methods suffer from an unacceptably hig...
Deep Learning ROC Curve DNA Copy Number Variations Humans Genome, Human False Positive Reactions Disease Area Under Curve Benchmarking Datasets as Topic
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Recent advances in network-based methods for disease gene prediction.

Briefings in bioinformatics Jul 20, 2021
Disease-gene association through genome-wide association study (GWAS) is an arduous task for researchers. Investigating single nucleotide polymorphisms that correlate with specific diseases needs statistical analysis of associations. Considering the ...
Genome-Wide Association Study Polymorphism, Single Nucleotide Disease Humans Machine Learning Databases, Nucleic Acid
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Deep-DRM: a computational method for identifying disease-related metabolites based on graph deep learning approaches.

Briefings in bioinformatics Jul 20, 2021
MOTIVATION: The functional changes of the genes, RNAs and proteins will eventually be reflected in the metabolic level. Increasing number of researchers have researched mechanism, biomarkers and targeted drugs by metabolites. However, compared with o...
Computational Biology Metabolism Neural Networks, Computer Disease Deep Learning Humans Gene Regulatory Networks
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Microbes and complex diseases: from experimental results to computational models.

Briefings in bioinformatics May 20, 2021
Studies have shown that the number of microbes in humans is almost 10 times that of cells. These microbes have been proven to play an important role in a variety of physiological processes, such as enhancing immunity, improving the digestion of gastr...
Disease Models, Biological Microbiota Humans Machine Learning Databases, Factual
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Predicting microRNA-disease associations from lncRNA-microRNA interactions via Multiview Multitask Learning.

Briefings in bioinformatics May 20, 2021
MOTIVATION: Identifying microRNAs that are associated with different diseases as biomarkers is a problem of great medical significance. Existing computational methods for uncovering such microRNA-diseases associations (MDAs) are mostly developed unde...
Models, Genetic MicroRNAs RNA, Long Noncoding Predictive Value of Tests Disease Humans Machine Learning
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MLCDForest: multi-label classification with deep forest in disease prediction for long non-coding RNAs.

Briefings in bioinformatics May 20, 2021
The long non-coding RNAs (lncRNAs) are subject of intensive recent studies due to its association with various human diseases. It is desirable to build the artificial intelligence-based models for prediction of diseases or tissues based on the lncRNA...
Computational Biology Models, Genetic RNA, Long Noncoding Humans Deep Learning Disease
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Deep learning in systems medicine.

Briefings in bioinformatics Mar 22, 2021
Systems medicine (SM) has emerged as a powerful tool for studying the human body at the systems level with the aim of improving our understanding, prevention and treatment of complex diseases. Being able to automatically extract relevant features nee...
Proteomics Metabolomics Disease Systems Analysis Transcriptome Deep Learning Genomics Precision Medicine Electronic Health Records Neural Networks, Computer Humans Algorithms Biomarkers
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Generative transfer learning for measuring plausibility of EHR diagnosis records.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2021
OBJECTIVE: Due to a complex set of processes involved with the recording of health information in the Electronic Health Records (EHRs), the truthfulness of EHR diagnosis records is questionable. We present a computational approach to estimate the pro...
Humans Disease Diagnosis Professional-Patient Relations Electronic Health Records Machine Learning Supervised Machine Learning Delivery of Health Care Probability
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The Human Phenotype Ontology in 2021.

Nucleic acids research Jan 8, 2021
The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for ...
Neonatal Screening Phenotype Animals International Cooperation Databases, Factual Pharmacogenetics Genome Terminology as Topic Infant, Newborn Genotype Internet Disease Humans Computational Biology Biological Ontologies Software Disease Models, Animal
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Machine Learning Approaches on High Throughput NGS Data to Unveil Mechanisms of Function in Biology and Disease.

Cancer genomics & proteomics Jan 1, 2021
In this review, the fundamental basis of machine learning (ML) and data mining (DM) are summarized together with the techniques for distilling knowledge from state-of-the-art omics experiments. This includes an introduction to the basic mathematical ...
Humans Machine Learning High-Throughput Nucleotide Sequencing Disease
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