[HTML][HTML] Computational pathology: a survey review and the way forward
Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …
developments of computational approaches to analyze and model medical histopathology …
[HTML][HTML] An aggregation of aggregation methods in computational pathology
Image analysis and machine learning algorithms operating on multi-gigapixel whole-slide
images (WSIs) often process a large number of tiles (sub-images) and require aggregating …
images (WSIs) often process a large number of tiles (sub-images) and require aggregating …
Risk-aware survival time prediction from whole slide pathological images
Deep-learning-based survival prediction can assist doctors by providing additional
information for diagnosis by estimating the risk or time of death. The former focuses on …
information for diagnosis by estimating the risk or time of death. The former focuses on …
Mutual-assistance learning for standalone mono-modality survival analysis of human cancers
Z Ning, Z Zhao, Q Feng, W Chen… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Current survival analysis of cancers confronts two key issues. While comprehensive
perspectives provided by data from multiple modalities often promote the performance of …
perspectives provided by data from multiple modalities often promote the performance of …
Single-Cell Spatial Analysis of Histopathology Images for Survival Prediction via Graph Attention Network
The tumor microenvironment is a complex ecosystem consisting of various immune and
stromal cells in addition to neoplastic cells. The spatial interaction and organization of these …
stromal cells in addition to neoplastic cells. The spatial interaction and organization of these …
From Pixels to Prognosis: A Survey on AI-Driven Cancer Patient Survival Prediction Using Digital Histology Images
Survival analysis is an integral part of medical statistics that is extensively utilized to
establish prognostic indices for mortality or disease recurrence, assess treatment efficacy …
establish prognostic indices for mortality or disease recurrence, assess treatment efficacy …
A Context Aware Lung Cancer Survival Prediction Network by Using Whole Slide Images
X Liu, Y Wang, Y Luo - International Conference on Neural Information …, 2023 - Springer
Lung cancer has caused enormous harm to human life and traditional whole slide image
(WSI) based lung cancer survival prediction methods suffer from information loss and can …
(WSI) based lung cancer survival prediction methods suffer from information loss and can …
CA 94304, USA
A Network, Z Li¹, Y Jiang, L Liu, Y Xia¹… - Applications of Medical …, 2023 - books.google.com
The tumor microenvironment is a complex ecosystem consisting of various immune and
stromal cells in addition to neoplastic cells. The spatial interaction and organization of these …
stromal cells in addition to neoplastic cells. The spatial interaction and organization of these …
AI and Pathology: Steering Treatment and Predicting Outcomes
R Gupta, J Kaczmarzyk, S Kobayashi… - … For Science: A Deep …, 2023 - books.google.com
The human body is constructed from over 1013 cells organized in complex patterns of
hierarchical organization. Each cell carries out its own metabolism. During various portions …
hierarchical organization. Each cell carries out its own metabolism. During various portions …
Deep learning-based discrete-time survival prediction on prostate cancer histopathology images
E Dietrich - 2022 - ediss.sub.uni-hamburg.de
In order to enable optimal treatment decisions, physicians can be supported by clinical
decision support systems. These aim at providing accurate and objective disease …
decision support systems. These aim at providing accurate and objective disease …