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Disease

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MLCDForest: multi-label classification with deep forest in disease prediction for long non-coding RNAs.

Briefings in bioinformatics
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...

Deep learning in systems medicine.

Briefings in bioinformatics
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...

Generative transfer learning for measuring plausibility of EHR diagnosis records.

Journal of the American Medical Informatics Association : JAMIA
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...

The Human Phenotype Ontology in 2021.

Nucleic acids research
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 ...

Machine Learning Approaches on High Throughput NGS Data to Unveil Mechanisms of Function in Biology and Disease.

Cancer genomics & proteomics
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 ...

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 ...

[Prognostic model of small sample critical diseases based on transfer learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Aiming at the problem that the small samples of critical disease in clinic may lead to prognostic models with poor performance of overfitting, large prediction error and instability, the long short-term memory transferring algorithm (transLSTM) was p...

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...

HerGePred: Heterogeneous Network Embedding Representation for Disease Gene Prediction.

IEEE journal of biomedical and health informatics
The discovery of disease-causing genes is a critical step towards understanding the nature of a disease and determining a possible cure for it. In recent years, many computational methods to identify disease genes have been proposed. However, making ...

Integrating ontologies of human diseases, phenotypes, and radiological diagnosis.

Journal of the American Medical Informatics Association : JAMIA
Mappings between ontologies enable reuse and interoperability of biomedical knowledge. The Radiology Gamuts Ontology (RGO)-an ontology of 16 918 diseases, interventions, and imaging observations-provides a resource for differential diagnosis and auto...