AIMC Topic: Inflammatory Bowel Diseases
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Multimodal deep learning applied to classify healthy and disease states of human microbiome.
Scientific reports
Jan 17, 2022
Metagenomic sequencing methods provide considerable genomic information regarding human microbiomes, enabling us to discover and understand microbial diseases. Compositional differences have been reported between patients and healthy people, which co...
DMFMDA: Prediction of Microbe-Disease Associations Based on Deep Matrix Factorization Using Bayesian Personalized Ranking.
IEEE/ACM transactions on computational biology and bioinformatics
Oct 7, 2021
Identifying the microbe-disease associations is conducive to understanding the pathogenesis of disease from the perspective of microbe. In this paper, we propose a deep matrix factorization prediction model (DMFMDA) based on deep neural network. Firs...
Web-based and machine learning approaches for identification of patient-reported outcomes in inflammatory bowel disease.
Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Sep 26, 2021
BACKGROUND: Messages from an Internet forum are raw material that emerges in a natural setting (i.e., non-induced by a research situation).
Role of Digital Health and Artificial Intelligence in Inflammatory Bowel Disease: A Scoping Review.
Genes
Sep 22, 2021
Inflammatory bowel diseases (IBD), subdivided into Crohn's disease (CD) and ulcerative colitis (UC), are chronic diseases that are characterized by relapsing and remitting periods of inflammation in the gastrointestinal tract. In recent years, the am...
Learning, visualizing and exploring 16S rRNA structure using an attention-based deep neural network.
PLoS computational biology
Sep 22, 2021
Recurrent neural networks with memory and attention mechanisms are widely used in natural language processing because they can capture short and long term sequential information for diverse tasks. We propose an integrated deep learning model for micr...
Machine Learning Modeling from Omics Data as Prospective Tool for Improvement of Inflammatory Bowel Disease Diagnosis and Clinical Classifications.
Genes
Sep 18, 2021
Research of inflammatory bowel disease (IBD) has identified numerous molecular players involved in the disease development. Even so, the understanding of IBD is incomplete, while disease treatment is still far from the precision medicine. Reliable di...
Translating polygenic risk scores for clinical use by estimating the confidence bounds of risk prediction.
Nature communications
Sep 6, 2021
A promise of genomics in precision medicine is to provide individualized genetic risk predictions. Polygenic risk scores (PRS), computed by aggregating effects from many genomic variants, have been developed as a useful tool in complex disease resear...
A machine learning approach identifies 5-ASA and ulcerative colitis as being linked with higher COVID-19 mortality in patients with IBD.
Scientific reports
Aug 13, 2021
Inflammatory bowel diseases (IBD), namely Crohn's disease (CD) and ulcerative colitis (UC) are chronic inflammation within the gastrointestinal tract. IBD patient conditions and treatments, such as with immunosuppressants, may result in a higher risk...
Artificial intelligence guided discovery of a barrier-protective therapy in inflammatory bowel disease.
Nature communications
Jul 12, 2021
Modeling human diseases as networks simplify complex multi-cellular processes, helps understand patterns in noisy data that humans cannot find, and thereby improves precision in prediction. Using Inflammatory Bowel Disease (IBD) as an example, here w...
Mice, Knockout
AMP-Activated Protein Kinases
Machine Learning
Disease Models, Animal
Organoids
Humans
Animals
Mice, Inbred C57BL
Multigene Family
Inflammatory Bowel Diseases
Artificial Intelligence
Molecular Targeted Therapy
Cohort Studies
Intestinal Mucosa
Gene Expression Regulation
Reproducibility of Results
Likelihood Functions
Mice
Dextran Sulfate
Treatment Outcome
Colitis
MiMeNet: Exploring microbiome-metabolome relationships using neural networks.
PLoS computational biology
May 17, 2021
The advance in microbiome and metabolome studies has generated rich omics data revealing the involvement of the microbial community in host disease pathogenesis through interactions with their host at a metabolic level. However, the computational too...
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