AI Medical Compendium Topic

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Disease

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mAML: an automated machine learning pipeline with a microbiome repository for human disease classification.

Database : the journal of biological databases and curation
Due to the concerted efforts to utilize the microbial features to improve disease prediction capabilities, automated machine learning (AutoML) systems aiming to get rid of the tediousness in manually performing ML tasks are in great demand. Here we d...

MosaicBase: A Knowledgebase of Postzygotic Mosaic Variants in Noncancer Disease-related and Healthy Human Individuals.

Genomics, proteomics & bioinformatics
Mosaic variants resulting from postzygotic mutations are prevalent in the human genome and play important roles in human diseases. However, except for cancer-related variants, there is no collection of postzygotic mosaic variants in noncancer disease...

Similar Disease Prediction With Heterogeneous Disease Information Networks.

IEEE transactions on nanobioscience
Studying the similarity of diseases can help us to explore the pathological characteristics of complex diseases, and help provide reliable reference information for inferring the relationship between new diseases and known diseases, so as to develop ...

iPiDA-sHN: Identification of Piwi-interacting RNA-disease associations by selecting high quality negative samples.

Computational biology and chemistry
As a large group of small non-coding RNAs (ncRNAs), Piwi-interacting RNAs (piRNAs) have been detected to be associated with various diseases. Identifying disease associated piRNAs can provide promising candidate molecular targets to promote the drug ...

Medical Information Extraction in the Age of Deep Learning.

Yearbook of medical informatics
OBJECTIVES: We survey recent developments in medical Information Extraction (IE) as reported in the literature from the past three years. Our focus is on the fundamental methodological paradigm shift from standard Machine Learning (ML) techniques to ...

Structuring, reuse and analysis of electronic dental data using the Oral Health and Disease Ontology.

Journal of biomedical semantics
BACKGROUND: A key challenge for improving the quality of health care is to be able to use a common framework to work with patient information acquired in any of the health and life science disciplines. Patient information collected during dental care...

Identifying disease trajectories with predicate information from a knowledge graph.

Journal of biomedical semantics
BACKGROUND: Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses that identify e.g. relationships between diseases. Some diseases are often dia...

Improving the accuracy of medical diagnosis with causal machine learning.

Nature communications
Machine learning promises to revolutionize clinical decision making and diagnosis. In medical diagnosis a doctor aims to explain a patient's symptoms by determining the diseases causing them. However, existing machine learning approaches to diagnosis...

Microbes and complex diseases: from experimental results to computational models.

Briefings in bioinformatics
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...

Predicting microRNA-disease associations from lncRNA-microRNA interactions via Multiview Multitask Learning.

Briefings in bioinformatics
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...