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Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data
Despite the remarkable advances in cancer diagnosis, treatment, and management over the
past decade, malignant tumors remain a major public health problem. Further progress in …
past decade, malignant tumors remain a major public health problem. Further progress in …
[HTML][HTML] Revolutionizing cancer research: the impact of artificial intelligence in digital biobanking
C Frascarelli, G Bonizzi, CR Musico, E Mane… - Journal of Personalized …, 2023 - mdpi.com
Background. Biobanks are vital research infrastructures aiming to collect, process, store, and
distribute biological specimens along with associated data in an organized and governed …
distribute biological specimens along with associated data in an organized and governed …
Quilt-1m: One million image-text pairs for histopathology
W Ikezogwo, S Seyfioglu, F Ghezloo… - Advances in neural …, 2023 - proceedings.neurips.cc
Recent accelerations in multi-modal applications have been made possible with the
plethora of image and text data available online. However, the scarcity of analogous data in …
plethora of image and text data available online. However, the scarcity of analogous data in …
[HTML][HTML] Data-driven color augmentation for H&E stained images in computational pathology
Computational pathology targets the automatic analysis of Whole Slide Images (WSI). WSIs
are high-resolution digitized histopathology images, stained with chemical reagents to …
are high-resolution digitized histopathology images, stained with chemical reagents to …
[HTML][HTML] A systematic comparison of deep learning methods for Gleason grading and scoring
Prostate cancer is the second most frequent cancer in men worldwide after lung cancer. Its
diagnosis is based on the identification of the Gleason score that evaluates the abnormality …
diagnosis is based on the identification of the Gleason score that evaluates the abnormality …
Digital examination of LYmph node CYtopathology using the Sydney system (DELYCYUS): an international, multi‐institutional study
Background After a series of standardized reporting systems in cytopathology, the Sydney
system was recently introduced to address the need for reproducibility and standardization …
system was recently introduced to address the need for reproducibility and standardization …
Interpretable classification of pathology whole-slide images using attention based context-aware graph convolutional neural network
M Liang, Q Chen, B Li, L Wang, Y Wang… - Computer methods and …, 2023 - Elsevier
Abstract Background and Objective Whole slide image (WSI) classification and lesion
localization within giga-pixel slide are challenging tasks in computational pathology that …
localization within giga-pixel slide are challenging tasks in computational pathology that …
From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non‐Invasive Precision Medicine in Cancer Patients
With the increasing demand for precision medicine in cancer patients, radiogenomics
emerges as a promising frontier. Radiogenomics is originally defined as a methodology for …
emerges as a promising frontier. Radiogenomics is originally defined as a methodology for …
Applications of self-supervised learning to biomedical signals: A survey
Over the last decade, deep learning applications in biomedical research have exploded,
demonstrating their ability to often outperform previous machine learning approaches in …
demonstrating their ability to often outperform previous machine learning approaches in …
Local-to-global spatial learning for whole-slide image representation and classification
Whole-slide image (WSI) provides an important reference for clinical diagnosis.
Classification with only WSI-level labels can be recognized for multi-instance learning (MIL) …
Classification with only WSI-level labels can be recognized for multi-instance learning (MIL) …