AIMC Topic: Multiomics

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Multiomics and eXplainable artificial intelligence for decision support in insulin resistance early diagnosis: A pediatric population-based longitudinal study.

Artificial intelligence in medicine
Pediatric obesity can drastically heighten the risk of cardiometabolic alterations later in life, with insulin resistance standing as the cornerstone linking adiposity to the increased cardiovascular risk. Puberty has been pointed out as a critical s...

scMaui: a widely applicable deep learning framework for single-cell multiomics integration in the presence of batch effects and missing data.

BMC bioinformatics
The recent advances in high-throughput single-cell sequencing have created an urgent demand for computational models which can address the high complexity of single-cell multiomics data. Meticulous single-cell multiomics integration models are requir...

Phenotype prediction using biologically interpretable neural networks on multi-cohort multi-omics data.

NPJ systems biology and applications
Integrating multi-omics data into predictive models has the potential to enhance accuracy, which is essential for precision medicine. In this study, we developed interpretable predictive models for multi-omics data by employing neural networks inform...

A novel assessment of whole-mount Gleason grading in prostate cancer to identify candidates for radical prostatectomy: a machine learning-based multiomics study.

Theranostics
: This study aims to assess whole-mount Gleason grading (GG) in prostate cancer (PCa) accurately using a multiomics machine learning (ML) model and to compare its performance with biopsy-proven GG (bxGG) assessment. : A total of 146 patients with PCa...

Deciphering dysregulation and CpG methylation in hepatocellular carcinoma using multi-omics and machine learning.

Epigenomics
This study investigates the altered expression and CpG methylation patterns of histone demethylase in hepatocellular carcinoma (HCC), aiming to uncover insights and promising diagnostics biomarkers. Leveraging TCGA-LIHC multi-omics data, we employe...

DeepDRA: Drug repurposing using multi-omics data integration with autoencoders.

PloS one
Cancer treatment has become one of the biggest challenges in the world today. Different treatments are used against cancer; drug-based treatments have shown better results. On the other hand, designing new drugs for cancer is costly and time-consumin...

Harnessing Artificial Intelligence in Multimodal Omics Data Integration: Paving the Path for the Next Frontier in Precision Medicine.

Annual review of biomedical data science
The integration of multiomics data with detailed phenotypic insights from electronic health records marks a paradigm shift in biomedical research, offering unparalleled holistic views into health and disease pathways. This review delineates the curre...