AIMC Topic: Disease Susceptibility

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Long Short-Term Memory Recurrent Neural Networks for Multiple Diseases Risk Prediction by Leveraging Longitudinal Medical Records.

IEEE journal of biomedical and health informatics
Individuals suffer from chronic diseases without being identified in time, which brings lots of burden of disease to the society. This paper presents a multiple disease risk prediction method to systematically assess future disease risks for patients...

Standard operating procedure for curation and clinical interpretation of variants in cancer.

Genome medicine
Manually curated variant knowledgebases and their associated knowledge models are serving an increasingly important role in distributing and interpreting variants in cancer. These knowledgebases vary in their level of public accessibility, and the co...

DeePathology: Deep Multi-Task Learning for Inferring Molecular Pathology from Cancer Transcriptome.

Scientific reports
Despite great advances, molecular cancer pathology is often limited to the use of a small number of biomarkers rather than the whole transcriptome, partly due to computational challenges. Here, we introduce a novel architecture of Deep Neural Network...

Prediction of Potential Drug-Disease Associations through Deep Integration of Diversity and Projections of Various Drug Features.

International journal of molecular sciences
Identifying new indications for existing drugs may reduce costs and expedites drug development. Drug-related disease predictions typically combined heterogeneous drug-related and disease-related data to derive the associations between drugs and disea...

Predicting lncRNA-disease associations using network topological similarity based on deep mining heterogeneous networks.

Mathematical biosciences
A kind of noncoding RNA with length more than 200 nucleotides named long noncoding RNA (lncRNA) has gained considerable attention in recent decades. Many studies have confirmed that human genome contains many thousands of lncRNAs. LncRNAs play signif...

Machine learning techniques for personalized breast cancer risk prediction: comparison with the BCRAT and BOADICEA models.

Breast cancer research : BCR
BACKGROUND: Comprehensive breast cancer risk prediction models enable identifying and targeting women at high-risk, while reducing interventions in those at low-risk. Breast cancer risk prediction models used in clinical practice have low discriminat...

Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs.

International journal of molecular sciences
Identification of disease-related microRNAs (disease miRNAs) is helpful for understanding and exploring the etiology and pathogenesis of diseases. Most of recent methods predict disease miRNAs by integrating the similarities and associations of miRNA...

Increased risk of group B Streptococcus causing meningitis in infants with mannose-binding lectin deficiency.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
OBJECTIVES: To evaluate the association of mannose-binding lectin (MBL) deficiency with susceptibility and clinical features of group B Streptococcus (GBS) causing meningitis in Chinese infants.

Enabling Precision Medicine through Integrative Network Models.

Journal of molecular biology
A key challenge in precision medicine lies in understanding molecular-level underpinnings of complex human disease. Biological networks in multicellular organisms can generate hypotheses about disease genes, pathways, and their behavior in disease-re...