Oncology/Hematology

Synergizing Deep Learning and Biological Heuristics for Extreme Long-Tail White Blood Cell Classification

Automated white blood cell (WBC) classification is essential for leukemia screening but remains challenged by extreme class imbalance, long-tail distributions, and domain shift, leading deep models to overfit dominant classes and fail on rare subtypes. We propose a hybrid framework for rare-class generalization that integrates a generative Pix2Pix-based restoration module for artifact removal, a S...

An Interpretable Machine Learning Framework for Non-Small Cell Lung Cancer Drug Response Analysis

Lung cancer is a condition where there is abnormal growth of malignant cells that spread in an uncontrollable fashion in the lungs. Some common treatment strategies are surgery, chemotherapy, and radiation which aren't the best options due to the heterogeneous nature of cancer. In personalized medicine, treatments are tailored according to the individual's genetic information along with lifestyle ...

Understanding Cell Fate Decisions with Temporal Attention

Understanding non-genetic determinants of cell fate is critical for developing and improving cancer therapies, as genetically identical cells can exhi...

An explainable boosting machine model for identifying artifacts caused by formalin-fixed paraffin embedding

Background: Formalin-fixed paraffin-embedding (FFPE) is a widely used, cost-effective method for long-term storage of clinical samples. However, fixat...

Clinical Priors Guided Lung Disease Detection in 3D CT Scans

Accurate classification of lung diseases from chest CT scans plays an important role in computer-aided diagnosis systems. However, medical imaging dat...

Towards Fair and Robust Volumetric CT Classification via KL-Regularised Group Distributionally Robust Optimisation

Automated diagnosis from chest computed tomography (CT) scans faces two persistent challenges in clinical deployment: distribution shift across acquis...

A Comprehensive Benchmark of Histopathology Foundation Models for Kidney Histopathology

Histopathology foundation models (HFMs), pretrained on large-scale cancer datasets, have advanced computational pathology. However, their applicabilit...

BiTro: Bidirectional Transfer Learning Enhances Bulk and Spatial Transcriptomics Prediction in Cancer Pathological Images

Cancer pathological analysis requires modeling tumor heterogeneity across multiple modalities, primarily through transcriptomics and whole slide imagi...

Clinical Priors Guided Lung Disease Detection in 3D CT Scans

Accurate classification of lung diseases from chest CT scans plays an important role in computer-aided diagnosis systems. However, medical imaging dat...

LUMINA: A Multi-Vendor Mammography Benchmark with Energy Harmonization Protocol

Publicly available full-field digital mammography (FFDM) datasets remain limited in size, clinical labels, and vendor diversity, which hinders the tra...

Artificial Intelligence in Mammography Screening in Norway (AIMS Norway): Protocol for a randomized controlled trial

Background and Objective: Increasing screening volumes, combined with global shortage of radiologists and a high proportion of normal mammograms, chal...

Predicting cognitive-behavioral therapy outcomes in obsessive-compulsive disorder from inhibitory control neural activity: A mega-analysis and machine learning study from the ENIGMA-OCD consortium

Objective Cognitive behavioral therapy (CBT) is an effective first-line treatment for obsessive-compulsive disorder (OCD), yet it remains difficult to...

Fair Lung Disease Diagnosis from Chest CT via Gender-Adversarial Attention Multiple Instance Learning

We present a fairness-aware framework for multi-class lung disease diagnosis from chest CT volumes, developed for the Fair Disease Diagnosis Challenge...

Diffusion-Based Feature Denoising and Using NNMF for Robust Brain Tumor Classification

Brain tumor classification from magnetic resonance imaging, which is also known as MRI, plays a sensitive role in computer-assisted diagnosis systems....

TumorCLIP: Lightweight Vision-Language Fusion for Explainable MRI-Based Brain Tumor Classification

Accurate classification of brain tumors from MRI is critical for guiding clinical decision-making; however, existing deep learning models are often hi...

Automated Segmentation of Head and Neck Cancer from CT Images Using 3D Convolutional Neural Networks

Head and neck cancer (HNC) requires accurate tumor delineation for effective radiotherapy planning. Manual segmentation of tumor regions is time-consu...

Facilitating genome annotation using ANNEXA and long-read RNA sequencing

With the advent of complete genome assemblies, genome annotation has become essential for the functional interpretation of genomic data. Long-read RNA...

Unmasking Biases and Reliability Concerns in Convolutional Neural Networks Analysis of Cancer Pathology Images

Convolutional Neural Networks have shown promising effectiveness in identifying different types of cancer from radiographs. However, the opaque nature...

mnDINO: Accurate and robust segmentation of micronuclei with vision transformer networks

Recent advances in cell segmentation successfully produce models that generalize across various cell-lines and imaging types. However, these methods s...

Benchmarking zero-shot single-cell foundation model embeddings for cellular dynamics reconstruction

Reconstructing cellular trajectories from time-resolved single-cell transcriptomics is fundamental to understanding processes from embryonic developme...