From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology

OSM El Nahhas, M van Treeck, G Wölflein, M Unger… - Nature …, 2025‏ - nature.com
Hematoxylin-and eosin-stained whole-slide images (WSIs) are the foundation of diagnosis
of cancer. In recent years, development of deep learning-based methods in computational …

Hest-1k: A dataset for spatial transcriptomics and histology image analysis

G Jaume, P Doucet, A Song, MY Lu… - Advances in …, 2025‏ - proceedings.neurips.cc
Spatial transcriptomics enables interrogating the molecular composition of tissue with ever-
increasing resolution and sensitivity. However, costs, rapidly evolving technology, and lack …

Bias in medical AI: Implications for clinical decision-making

JL Cross, MA Choma, JA Onofrey - PLOS Digital Health, 2024‏ - journals.plos.org
Biases in medical artificial intelligence (AI) arise and compound throughout the AI lifecycle.
These biases can have significant clinical consequences, especially in applications that …

[HTML][HTML] Immune subty** of melanoma whole slide images using multiple instance learning

L Godson, N Alemi, J Nsengimana, GP Cook… - Medical Image …, 2024‏ - Elsevier
Determining early-stage prognostic markers and stratifying patients for effective treatment
are two key challenges for improving outcomes for melanoma patients. Previous studies …

Predicting the tumor microenvironment composition and immunotherapy response in non-small cell lung cancer from digital histopathology images

S Patkar, A Chen, A Basnet, A Bixby… - NPJ Precision …, 2024‏ - nature.com
Immune checkpoint inhibitors (ICI) have become integral to treatment of non-small cell lung
cancer (NSCLC). However, reliable biomarkers predictive of immunotherapy efficacy are …