A roadmap for multi-omics data integration using deep learning
High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …
amount of multi-omics data for various applications. These data have revolutionized …
Deep learning for survival analysis: a review
The influx of deep learning (DL) techniques into the field of survival analysis in recent years
has led to substantial methodological progress; for instance, learning from unstructured or …
has led to substantial methodological progress; for instance, learning from unstructured or …
[HTML][HTML] Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review
L Schneider, S Laiouar-Pedari, S Kuntz… - European journal of …, 2022 - Elsevier
Background Over the past decade, the development of molecular high-throughput methods
(omics) increased rapidly and provided new insights for cancer research. In parallel, deep …
(omics) increased rapidly and provided new insights for cancer research. In parallel, deep …
Deep-learning-based prediction of late age-related macular degeneration progression
Both genetic and environmental factors influence the etiology of age-related macular
degeneration (AMD), a leading cause of blindness. AMD severity is primarily measured by …
degeneration (AMD), a leading cause of blindness. AMD severity is primarily measured by …
Emerging applications of machine learning in genomic medicine and healthcare
The integration of artificial intelligence technologies has propelled the progress of clinical
and genomic medicine in recent years. The significant increase in computing power has …
and genomic medicine in recent years. The significant increase in computing power has …
HFBSurv: hierarchical multimodal fusion with factorized bilinear models for cancer survival prediction
Motivation Cancer survival prediction can greatly assist clinicians in planning patient
treatments and improving their life quality. Recent evidence suggests the fusion of …
treatments and improving their life quality. Recent evidence suggests the fusion of …
A convolutional neural network model for survival prediction based on prognosis-related cascaded Wx feature selection
Great advances in deep learning have provided effective solutions for prediction tasks in the
biomedical field. However, accurate prognosis prediction using cancer genomics data …
biomedical field. However, accurate prognosis prediction using cancer genomics data …
PAGE-Net: interpretable and integrative deep learning for survival analysis using histopathological images and genomic data
J Hao, SC Kosaraju, NZ Tsaku, DH Song… - Pacific Symposium on …, 2019 - World Scientific
The integration of multi-modal data, such as histopathological images and genomic data, is
essential for understanding cancer heterogeneity and complexity for personalized …
essential for understanding cancer heterogeneity and complexity for personalized …
Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data
Background Understanding the complex biological mechanisms of cancer patient survival
using genomic and clinical data is vital, not only to develop new treatments for patients, but …
using genomic and clinical data is vital, not only to develop new treatments for patients, but …
Genome‐wide association study‐based deep learning for survival prediction
Informative and accurate survival prediction with individualized dynamic risk profiles over
time is critical for personalized disease prevention and clinical management. The massive …
time is critical for personalized disease prevention and clinical management. The massive …