Deep learning in cancer genomics and histopathology

Histopathology and genomic profiling are cornerstones of precision oncology and are routinely obtained for patients with cancer.

A systematic analysis of deep learning in genomics and ... - NCBI

A distinct feature of DL in histopathology is the diverse range of cancer tissues studied. In contrast, DL studies in genomics primarily focus ...

Deep learning in cancer pathology: a new generation of clinical ...

Advances in deep learning (DL), an artificial intelligence (AI) technology, have enabled the extraction of previously hidden information ...

(PDF) Deep learning in cancer genomics and histopathology

Genomic profiling has revolutionized cancer diagnosis and classification by surpassing the limitations of traditional histopathology methods [45] ...

A systematic analysis of deep learning in genomics and ... - PubMed

Background: Digitized histopathological tissue slides and genomics profiling data are available for many patients with solid tumors. In the last ...

Deep learning integrates histopathology and proteogenomics at a ...

Article. Deep learning integrates histopathology and proteogenomics at a pan-cancer level.

Self-supervised attention-based deep learning for pan-cancer ...

The histopathological phenotype of tumors reflects the underlying genetic makeup. Deep learning can predict genetic alterations from ...

Deep learning in cancer diagnosis, prognosis and treatment selection

A variety of DL approaches that utilise a combination of genomic, transcriptomic or histopathology data have been applied in clinical and ...

Exploring Histological Similarities Across Cancers From a Deep ...

Histopathology image analysis is widely accepted as a gold standard for cancer diagnosis. The Cancer Genome Atlas (TCGA) contains large repositories of ...

Predicting cancer outcomes from histology and genomics using ...

We developed a computational approach based on deep learning to predict the overall survival of patients diagnosed with brain tumors from microscopic images.

Pan-cancer integrative histology-genomic analysis via multimodal ...

Our weakly supervised, multimodal deep-learning algorithm is able to fuse these heterogeneous modalities to predict outcomes and discover ...

Integration of deep learning-based image analysis and genomic ...

In parallel, deep learning approaches revealed the enormous potential for medical image analysis, especially in digital pathology. Combining image and omics ...

Deep learning integrates histopathology and proteogenomics at a ...

Deep learning integrates histopathology and proteogenomics at a pan-cancer level. ; Date Published. 08/2023 ; ISSN. 2666-3791 ; DOI. 10.1016/j.xcrm.2023.101173.

Artificial Intelligence in cancer pathology—hope or hype? - The Lancet

uses artificial intelligence (AI) to infer somatic molecular changes (of both genome and proteome) from digital images of colorectal cancers.

Deep learning-based survival prediction for multiple cancer types ...

We developed a deep learning system (DLS) to predict disease specific survival across 10 cancer types from The Cancer Genome Atlas (TCGA).

Deep learning in cancer genomics and histopathology - a-z.lu

Histopathology and genomic profiling are cornerstones of precision oncology and are routinely obtained for patients with cancer.

A systematic analysis of deep learning in genomics and ... - OUCI

Abstract Background Digitized histopathological tissue slides and genomics profiling data are available for many patients with solid tumors.

(PDF) Deep learning in cancer diagnosis, prognosis and treatment ...

We focus on the deep learning applications for omics data types, including genomic, methylation and transcriptomic data, as well as ...

hist2RNA: An Efficient Deep Learning Architecture to Predict Gene ...

In this paper, we propose a new deep learning method for gene expression prediction from breast cancer histopathology images that requires substantially less ...

Harnessing TME depicted by histological images to improve cancer ...

In this study, we provide a powerful deep learning system to augment TME information based on histological images for patients without ST data, thereby ...