Racial/ethnic and gender disparities in perceived stress and physical activity in college

Cheng, Chia-Hsin; Kazemi, Sanam; Baker, Michael; Weiss, Jie W

doi:10.1080/07448481.2022.2155461

Cited by 1 publication

(1 citation statement)

References 30 publications

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“…EV-GCN, a population-based disease analysis method uses multi-modal medical data to evaluate the proposed method. In another recent study, a weighted-link GNN algorithm that combined graph auto-encoder and graph convolutional network was put forward ( Cheng et al, 2023 ). The algorithm produced the best classification performance in the lung cancer knowledge classification compared to other state-of-the-art methods.…”

Section: Multi-omics Data Integration Interpretation and Disease Pred...mentioning

confidence: 99%

A review of multi-omics data integration through deep learning approaches for disease diagnosis, prognosis, and treatment

Wekesa

Kimwele

2023

Front. Genet.

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Accurate diagnosis is the key to providing prompt and explicit treatment and disease management. The recognized biological method for the molecular diagnosis of infectious pathogens is polymerase chain reaction (PCR). Recently, deep learning approaches are playing a vital role in accurately identifying disease-related genes for diagnosis, prognosis, and treatment. The models reduce the time and cost used by wet-lab experimental procedures. Consequently, sophisticated computational approaches have been developed to facilitate the detection of cancer, a leading cause of death globally, and other complex diseases. In this review, we systematically evaluate the recent trends in multi-omics data analysis based on deep learning techniques and their application in disease prediction. We highlight the current challenges in the field and discuss how advances in deep learning methods and their optimization for application is vital in overcoming them. Ultimately, this review promotes the development of novel deep-learning methodologies for data integration, which is essential for disease detection and treatment.

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Section: Multi-omics Data Integration Interpretation and Disease Pred...mentioning

confidence: 99%

A review of multi-omics data integration through deep learning approaches for disease diagnosis, prognosis, and treatment

Wekesa

Kimwele

2023

Front. Genet.

View full text Add to dashboard Cite

show abstract

Racial/ethnic and gender disparities in perceived stress and physical activity in college

Cited by 1 publication

References 30 publications

A review of multi-omics data integration through deep learning approaches for disease diagnosis, prognosis, and treatment

A review of multi-omics data integration through deep learning approaches for disease diagnosis, prognosis, and treatment

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