Research Articles
Decoding the Cancer Stem Cell Code: A Comparative Analysis of CSC vs Normal Stem Cell Molecular Signatures for Targeted Therapies
This article provides a comprehensive comparative analysis of the distinct molecular signatures that define Cancer Stem Cells (CSCs) and normal stem cells.
Transformer Architectures for Slide-Level Representation Learning: A Comprehensive Guide for Biomedical AI
This article provides a comprehensive exploration of transformer-based models for slide-level representation learning in computational pathology.
Optimizing Computational Pathology: Knowledge Distillation for Efficient and Robust Foundation Models
This article explores the transformative role of knowledge distillation (KD) in advancing computational pathology foundation models.
Zero-Shot Visual-Language Foundation Models in Pathology: A New Paradigm for AI-Driven Diagnosis
This article explores the transformative potential of visual-language foundation models (VLFMs) for zero-shot classification in computational pathology.
Foundation Models for Biomarker Prediction from H&E Slides: Methods, Applications, and Clinical Translation
This article explores the transformative role of foundation models in predicting biomarkers directly from routine H&E-stained histopathology slides.
Applying DINOv2 Self-Supervised Learning to Pathology Images: A Comprehensive Guide for Biomedical Research
This article provides a comprehensive exploration of applying the DINOv2 self-supervised learning model to computational pathology.
Foundation Models for Weakly Supervised Whole Slide Image Classification: A Comprehensive Guide for Biomedical Research
This article provides a comprehensive exploration of using foundation models for weakly supervised classification of histopathological Whole Slide Images (WSIs).
Vision-Language Pretraining for Histopathology: Advances in Image-Text Retrieval and Biomarker Discovery
This article explores the transformative potential of vision-language pretraining (VLP) models in computational pathology for histopathology image-text retrieval.
Few-Shot Learning for Pathology Foundation Models: A Guide to Implementation, Challenges, and Future Directions
This article provides a comprehensive guide for researchers and drug development professionals on implementing few-shot learning (FSL) with pathology foundation models (PFMs).
Fine-Tuning Foundation Models for Rare Cancer Classification: Overcoming Data Scarcity with Advanced AI
This article provides a comprehensive guide for researchers and drug development professionals on applying fine-tuning techniques to foundation models for the classification of rare cancers.