Cargando…

Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication

BACKGROUND: Deep learning models can infer cancer patient prognosis from molecular and anatomic pathology information. Recent studies that leveraged information from complementary multimodal data improved prognostication, further illustrating the potential utility of such methods. However, current a...

Descripción completa

Detalles Bibliográficos
Autores principales:	Azher, Zarif L., Suvarna, Anish, Chen, Ji-Qing, Zhang, Ze, Christensen, Brock C., Salas, Lucas A., Vaickus, Louis J., Levy, Joshua J.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2023
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10363299/ https://www.ncbi.nlm.nih.gov/pubmed/37481666 http://dx.doi.org/10.1186/s13040-023-00338-w

Ejemplares similares

PathFlowAI: A High-Throughput Workflow for Preprocessing, Deep Learning and Interpretation in Digital Pathology
por: Levy, Joshua J., et al.
Publicado: (2020)

Inferring spatial transcriptomics markers from whole slide images to characterize metastasis-related spatial heterogeneity of colorectal tumors: A pilot study
por: Fatemi, Michael, et al.
Publicado: (2023)

Topological Feature Extraction and Visualization of Whole Slide Images using Graph Neural Networks
por: Levy, Joshua, et al.
Publicado: (2021)

Comparison of machine-learning algorithms for the prediction of Current Procedural Terminology (CPT) codes from pathology reports
por: Levy, Joshua, et al.
Publicado: (2022)

Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study
por: Levy, Joshua J., et al.
Publicado: (2021)

To pretrain or not? A systematic analysis of the benefits of pretraining in diabetic retinopathy
por: Srinivasan, Vignesh, et al.
Publicado: (2022)

Cough event classification by pretrained deep neural network
por: Liu, Jia-Ming, et al.
Publicado: (2015)

MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks
por: Levy, Joshua J., et al.
Publicado: (2021)

Enhanced Tooth Region Detection Using Pretrained Deep Learning Models
por: Al-Sarem, Mohammed, et al.
Publicado: (2022)

Mixed Effects Machine Learning Models for Colon Cancer Metastasis Prediction using Spatially Localized Immuno-Oncology Markers
por: Levy, Joshua J., et al.
Publicado: (2022)

MethylNet: an automated and modular deep learning approach for DNA methylation analysis
por: Levy, Joshua J., et al.
Publicado: (2020)

An Empirical Analysis of an Optimized Pretrained Deep Learning Model for COVID-19 Diagnosis
por: Sangeetha, S. K. B., et al.
Publicado: (2022)

Editorial: Artificial intelligence: applications in clinical medicine
por: Levy, Joshua, et al.
Publicado: (2023)

An Improved Math Word Problem (MWP) Model Using Unified Pretrained Language Model (UniLM) for Pretraining
por: Zhang, Dongqiu, et al.
Publicado: (2022)

HiTAIC: hierarchical tumor artificial intelligence classifier traces tissue of origin and tumor type in primary and metastasized tumors using DNA methylation
por: Zhang, Ze, et al.
Publicado: (2023)

A Pretraining-Retraining Strategy of Deep Learning Improves Cell-Specific Enhancer Predictions
por: Niu, Xiaohui, et al.
Publicado: (2020)

Predictive performance of radiomic models based on features extracted from pretrained deep networks
por: Demircioğlu, Aydin
Publicado: (2022)

Deep Features from Pretrained Networks Do Not Outperform Hand-Crafted Features in Radiomics
por: Demircioğlu, Aydin
Publicado: (2023)

Gastrointestinal Tract Disease Classification from Wireless Endoscopy Images Using Pretrained Deep Learning Model
por: Yogapriya, J., et al.
Publicado: (2021)

Development and external validation of a pretrained deep learning model for the prediction of non-accidental trauma
por: Huang, David, et al.
Publicado: (2023)

Pretrained Transformer Language Models Versus Pretrained Word Embeddings for the Detection of Accurate Health Information on Arabic Social Media: Comparative Study
por: Albalawi, Yahya, et al.
Publicado: (2022)

A large-scale internal validation study of unsupervised virtual trichrome staining technologies on nonalcoholic steatohepatitis liver biopsies
por: Levy, Joshua J., et al.
Publicado: (2020)

Document Network Projection in Pretrained Word Embedding Space
por: Gourru, Antoine, et al.
Publicado: (2020)

Visual-Text Reference Pretraining Model for Image Captioning
por: Li, Pengfei, et al.
Publicado: (2022)

Heuristic Attention Representation Learning for Self-Supervised Pretraining
por: Tran, Van Nhiem, et al.
Publicado: (2022)

Medical image captioning via generative pretrained transformers
por: Selivanov, Alexander, et al.
Publicado: (2023)

Acute Lymphoblastic Leukemia Detection and Classification of Its Subtypes Using Pretrained Deep Convolutional Neural Networks
por: Shafique, Sarmad, et al.
Publicado: (2018)

Clinical Named Entity Recognition from Chinese Electronic Medical Records Based on Deep Learning Pretraining
por: Gong, Lejun, et al.
Publicado: (2020)

AptaTrans: a deep neural network for predicting aptamer-protein interaction using pretrained encoders
por: Shin, Incheol, et al.
Publicado: (2023)

DNA 5-hydroxymethylcytosine in pediatric central nervous system tumors may impact tumor classification and is a positive prognostic marker
por: Azizgolshani, Nasim, et al.
Publicado: (2021)

Deep Neural Network-Based Automatic Dicentric Chromosome Detection Using a Model Pretrained on Common Objects
por: Kim, Kangsan, et al.
Publicado: (2023)

Critical Analysis of Deconfounded Pretraining to Improve Visio-Linguistic Models
por: Cornille, Nathan, et al.
Publicado: (2022)

Diagnosis of Lumbar Spondylolisthesis Using Optimized Pretrained CNN Models
por: Saravagi, Deepika, et al.
Publicado: (2022)

Pretraining strategies for effective promoter-driven gene expression prediction
por: Reddy, Aniketh Janardhan, et al.
Publicado: (2023)

Sequence-to-sequence pretraining for a less-resourced Slovenian language
por: Ulčar, Matej, et al.
Publicado: (2023)

Pretrained transformer models for predicting the withdrawal of drugs from the market
por: Mazuz, Eyal, et al.
Publicado: (2023)

Denoise Pretraining on Nonequilibrium Molecules for Accurate and Transferable Neural Potentials
por: Wang, Yuyang, et al.
Publicado: (2023)

EpiGePT: a Pretrained Transformer model for epigenomics
por: Gao, Zijing, et al.
Publicado: (2023)

WaSP-ECG: A Wave Segmentation Pretraining Toolkit for Electrocardiogram Analysis
por: Brisk, Rob, et al.
Publicado: (2022)

AppendiXNet: Deep Learning for Diagnosis of Appendicitis from A Small Dataset of CT Exams Using Video Pretraining
por: Rajpurkar, Pranav, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_uh96dgtso8n8cr0m14or9q2t3d