AIMC Topic: Disease

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FedOSS: Federated Open Set Recognition via Inter-Client Discrepancy and Collaboration.

IEEE transactions on medical imaging Jan 2, 2024
Open set recognition (OSR) aims to accurately classify known diseases and recognize unseen diseases as the unknown class in medical scenarios. However, in existing OSR approaches, gathering data from distributed sites to construct large-scale central...
Machine Learning Software Disease Humans
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Predicting pathogenic protein variants.

Science (New York, N.Y.) Sep 19, 2023
Machine-learning algorithm uses structure prediction to spot disease-causing mutations.
Protein Conformation Disease Mutation, Missense Machine Learning Sequence Analysis, DNA Mutant Proteins Algorithms Genetic Variation
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CFNCM: Collaborative filtering neighborhood-based model for predicting miRNA-disease associations.

Computers in biology and medicine Jun 9, 2023
MicroRNAs have a significant role in the emergence of various human disorders. Consequently, it is essential to understand the existing interactions between miRNAs and diseases, as this will help scientists better study and comprehend the diseases' b...
Neighborhood Characteristics MicroRNAs Algorithms Humans Disease Computer Simulation Support Vector Machine
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Overcoming regional limitations: transfer learning for cross-regional microbial-based diagnosis of diseases.

Gut Oct 28, 2022
Humans Machine Learning Gastrointestinal Microbiome Disease
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Nested epistasis enhancer networks for robust genome regulation.

Science (New York, N.Y.) Aug 11, 2022
Mammalian genomes have multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, but it is unclear how these enhancers coordinate to achieve this task. We combine multiplexed CRISPRi screening with machine learning t...
Disease K562 Cells Cell Cycle Proteins Nuclear Proteins Transcription Factors Epistasis, Genetic Enhancer Elements, Genetic Machine Learning Genome-Wide Association Study Humans
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Role of Deep Learning in Predicting Aging-Related Diseases: A Scoping Review.

Cells Oct 28, 2021
Aging refers to progressive physiological changes in a cell, an organ, or the whole body of an individual, over time. Aging-related diseases are highly prevalent and could impact an individual's physical health. Recently, artificial intelligence (AI)...
Disease Humans Aging Deep Learning Neural Networks, Computer
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Disease variant prediction with deep generative models of evolutionary data.

Nature Oct 27, 2021
Quantifying the pathogenicity of protein variants in human disease-related genes would have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of these variants still have unknown consequences. In principle, computational...
Selection, Genetic Genetic Fitness Genetic Variation Disease Bayes Theorem Biological Assay Genetic Predisposition to Disease Evolution, Molecular Humans Unsupervised Machine Learning Proteins Phenotype Models, Molecular
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Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network.

American journal of human genetics Sep 15, 2021
Rare diseases affect millions of people worldwide, and discovering their genetic causes is challenging. More than half of the individuals analyzed by the Undiagnosed Diseases Network (UDN) remain undiagnosed. The central hypothesis of this work is th...
Humans Rare Diseases Multifactorial Inheritance Undiagnosed Diseases Genomics Machine Learning Phenotype Databases, Genetic Disease
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Permutation-based identification of important biomarkers for complex diseases via machine learning models.

Nature communications May 21, 2021
Study of human disease remains challenging due to convoluted disease etiologies and complex molecular mechanisms at genetic, genomic, and proteomic levels. Many machine learning-based methods have been developed and widely used to alleviate some anal...
Machine Learning Support Vector Machine Neoplasms Disease Humans Algorithms Proteomics Neural Networks, Computer Biomarkers
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Development of machine learning model for diagnostic disease prediction based on laboratory tests.

Scientific reports Apr 7, 2021
The use of deep learning and machine learning (ML) in medical science is increasing, particularly in the visual, audio, and language data fields. We aimed to build a new optimized ensemble model by blending a DNN (deep neural network) model with two ...
Diagnosis, Computer-Assisted ROC Curve Machine Learning Disease Deep Learning Databases, Factual Humans Clinical Laboratory Techniques Neural Networks, Computer
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