Article

Deep learning supported discovery of biomarkers for clinical prognosis of liver cancer

2024-03-19

Abstract excerpt

<title>Abstract</title> <p>Tissue biomarkers are crucial for cancer diagnosis, prognosis assessment, and treatment planning. However, there are few known biomarkers that are robust enough to show true analytical and clinical value. Deep learning (DL)-based computational pathology can be used as a strategy to predict survival, but the limited interpretability and generalizability prevent acceptance in clinical pra...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: f27d96eb-9c62-54dc-b039-21dde79a8e5a
DOI: 10.21203/rs.3.rs-1452983/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Deep learning supported discovery of biomarkers for clinical prognosis of liver cancerDOI 10.21203/rs.3.rs-1452983/v1Read

AI inspired discovery of new biomarkers for clinical prognosis of liver cancerSemantic proximity Read

Exploring prognostic indicators in the pathological images of hepatocellular carcinoma based on deep learning.Semantic proximity Read

From slides to insights: Harnessing deep learning for prognostic survival prediction in human colorectal cancer histologySemantic proximity Read

Enhancing Histological Cancer Cell Detection: Integrating XAI with Deep Learning for Improved Accuracy, Interpretability, and Clinical TrustSemantic proximity Read

Deep learning can predict multi-omic biomarkers from routine pathology images: A systematic large-scale studySemantic proximity Read

Two-stage biologically interpretable neural-network models for liver cancer prognosis prediction using histopathology and transcriptomic dataSemantic proximity Read

Predicting Primary Site of Secondary Liver Cancer with a Neural Estimator of Metastatic Origin (NEMO)Semantic proximity Read

Transformer with convolution and graph-node co-embedding: An accurate and interpretable vision backbone for predicting gene expressions from local histopathological image.Semantic proximity Read

Interpretable multimodal deep learning for real-time pan-tissue pan-disease pathology search on social mediaSemantic proximity Read

A systematic analysis of deep learning in genomics and histopathology for precision oncology.Semantic proximity Read

Utilizing Deep Neural Networks in Digital Pathology: Enhancing Accuracy and Speed in Colorectal Cancer DiagnosisSemantic proximity Read

PAI-WSIT: a Comprehensive Curated Resource for Cancerous Pathology With Deep LearningSemantic proximity Read