Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data

G Lorenzo, SR Ahmed, DA Hormuth II… - Annual Review of …, 2024‏ - annualreviews.org
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 …

[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 …

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 …

[HTML][HTML] Data-driven color augmentation for H&E stained images in computational pathology

N Marini, S Otalora, M Wodzinski, S Tomassini… - Journal of Pathology …, 2023‏ - Elsevier
Computational pathology targets the automatic analysis of Whole Slide Images (WSI). WSIs
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

JP Dominguez-Morales, L Duran-Lopez, N Marini… - Medical Image …, 2024‏ - Elsevier
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 …

Digital examination of LYmph node CYtopathology using the Sydney system (DELYCYUS): an international, multi‐institutional study

A Caputo, F Fraggetta, P Cretella… - Cancer …, 2023‏ - Wiley Online Library
Background After a series of standardized reporting systems in cytopathology, the Sydney
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 …

From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non‐Invasive Precision Medicine in Cancer Patients

Y Guo, T Li, B Gong, Y Hu, S Wang, L Yang… - Advanced …, 2025‏ - Wiley Online Library
With the increasing demand for precision medicine in cancer patients, radiogenomics
emerges as a promising frontier. Radiogenomics is originally defined as a methodology for …

Applications of self-supervised learning to biomedical signals: A survey

F Del Pup, M Atzori - IEEE Access, 2023‏ - ieeexplore.ieee.org
Over the last decade, deep learning applications in biomedical research have exploded,
demonstrating their ability to often outperform previous machine learning approaches in …

Local-to-global spatial learning for whole-slide image representation and classification

J Yu, T Ma, Y Fu, H Chen, M Lai, C Zhuo… - … medical imaging and …, 2023‏ - Elsevier
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) …