2 citations · 3 across the 7 of their papers we have counts for
8 papers
Multimodal Analysis of White Blood Cell Differentiation in Acute Myeloid Leukemia Patients using a β-Variational Autoencoder
Gizem Mert, Ario Sadafi, Raheleh Salehi +2
Biomedical imaging and RNA sequencing with single-cell resolution improves our understanding of white blood cell diseases like leukemia. By combining morphological and transcriptom…
A Continual Learning Approach for Cross-Domain White Blood Cell Classification
Ario Sadafi, Raheleh Salehi, Armin Gruber +4
Accurate classification of white blood cells in peripheral blood is essential for diagnosing hematological diseases. Due to constantly evolving clinical settings, data sources, and…
A Study of Age and Sex Bias in Multiple Instance Learning based Classification of Acute Myeloid Leukemia Subtypes
Ario Sadafi, Matthias Hehr, Nassir Navab +1
Accurate classification of Acute Myeloid Leukemia (AML) subtypes is crucial for clinical decision-making and patient care. In this study, we investigate the potential presence of a…
Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images
Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar +5
Explainability is a key requirement for computer-aided diagnosis systems in clinical decision-making. Multiple instance learning with attention pooling provides instance-level expl…
BEL: A Bag Embedding Loss for Transformer enhances Multiple Instance Whole Slide Image Classification
Daniel Sens, Ario Sadafi, Francesco Paolo Casale +2
Multiple Instance Learning (MIL) has become the predominant approach for classification tasks on gigapixel histopathology whole slide images (WSIs). Within the MIL framework, singl…
Active Learning Enhances Classification of Histopathology Whole Slide Images with Attention-based Multiple Instance Learning
Ario Sadafi, Nassir Navab, Carsten Marr
In many histopathology tasks, sample classification depends on morphological details in tissue or single cells that are only visible at the highest magnification. For a pathologist…