Oncology/Hematology

Atlas H&E-TME: Scalable AI-Based Tissue Profiling at Expert Pathologist-Level Accuracy

Hematoxylin and eosin (H&E) staining is the cornerstone of histopathology, yet scalable, quantitative analysis of H&E whole-slide images (WSIs) remains a central challenge in computational pathology. We present Atlas H&E-TME, an AI-based system built on the Atlas family of pathology foundation models that predicts tissue quality, tissue region, and cell type labels across multiple cancer types, yi...

Intelligent Skin Cancer Detection Using a Multispectral Metasurface and a Hybrid

Skin cancer is among the most prevalent malignancies worldwiAdbe satnradcitts early detection is essential for improving patient survival and reducing treatment costs Conventional dermoscopic and visual imaging techniques are primarily limited to the visible spectrum and often fail to capture subtle spectral signatures associated with early stage malignancies This study proposes an innovative fram...

SHERLOC: An interpretable deep learning model for longitudinal circulating tumor DNA data in survival analysis

Longitudinal circulating tumor DNA (ctDNA) measurements offer a noninvasive means to monitor treatment response, but clinical trial data present subst...

Patient-Level Diagnosis of Acute Myeloid Leukemia via Deep Learning Analysis of Bone Marrow Smear

Bone marrow smear review remains important for acute myeloid leukemia (AML) assessment, but manual single-cell interpretation is labor-intensive and p...

OncoTraj: a public benchmark for longitudinal resistance prediction in EGFR-mutant non-small-cell lung cancer on osimertinib

Resistance to first-line osimertinib in EGFR-mutant non-small-cell lung cancer (NSCLC) is the canonical example of predictable clonal evolution under ...

Improving PET/CT-Based Whole-Body Lesion Segmentation Using Prediction Uncertainty-Augmented Models

Accurate lesion segmentation from whole-body Positron Emission Tomography (PET)/Computed Tomography (CT) scans is essential for cancer staging and tre...

Segmentation-Assisted Brain MRI Synthesis with Cross-Image Multi-Contrast Feature Memory Bank Retrieval Augmentation

Multi-contrast brain MRI provide complementary soft-tissue characteristics that aid in the screening and diagnosis of diseases. However, limited scann...

Querying Counterfactuals on Tissue Graphs with Supervised Disentanglement

\textit{Tissue graph counterfactuals} ask how a cell's expression would change under altered spatial neighbor contexts. Such queries are central to pr...

Routine laboratory trajectories encode the onset of organ-level complications in cancer

Routine laboratory panels drawn during cancer treatment constitute longitudinal physiological recordings of organ function, yet their temporal structu...

Single-cell gene regulatory network reconstruction and key regulator identification using a dual-channel fusion graph convolutional network

Background and objective: Gene regulatory networks are formed by complex regulatory relationships between transcription factors and their target genes...

A Web-based software toolkit for accessible and best-practice machine learning analyses in biomedical research

Machine learning is increasingly central to biomedical research, but using machine learning well often requires substantial computational expertise an...

Cell type-centric interaction networks define spatial architecture of intrahepatic cholangiocarcinoma

Tumor spatial organization critically shapes disease progression and therapeutic response, yet remains poorly defined. Intrahepatic cholangiocarcinoma...

HOPE: Interpretable Histology Analysis with Spatial Omics-Derived Signatures for Precision Oncology

Hematoxylin and eosin (H&E) stained images are fundamental clinical tools for disease assessment. However, even with advanced computational models, th...

Single-Cell Multi-Omics Dissection of Malignant Evolutionary Mechanisms and Construction of a Prognostic Model for Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) exhibits pronounced heterogeneity across WHO histological grades, yet systematic single-cell multi-omics studi...

Explaining Unsupervised Disease Staging in Huntington's Disease: Insights into Model Representations and Clusters

Huntington's disease (HD) is a progressive neurodegenerative disorder that affects motor, cognitive, and behavioral functions, where accurate characte...

Mitosis Detection in the Wild: Multi-Tumor and Context-Aware Generalization in the MIDOG 2025 Challenge

Automated mitosis detection is a well-established task in computational pathology. While previous benchmarks focused on scanner-induced domain shift, ...

Multimodal sleep stage classification and label-free abnormality scoring in mid-to-older adults

Background: Sleep fragmentation and reduced sleep efficiency are markers of disrupted sleep architecture linked to cognitive and age-related decline. ...

Quantifying Cancer Clinical Trial Eligibility Using Artificial Intelligence-Based Matching

PURPOSE: To develop and validate an artificial intelligence-enabled platform that converts unstructured cancer trial eligibility criteria into structu...

A Machine Learning-Based Framework for Discovering Huntington's Disease Stages: Integrating Graph Representation Learning and clustering to Uncover Progression Dynamics in Longitudinal Enroll-HD Dataset

Huntington's disease (HD) is a progressive brain disorder that gradually affects movement, cognitive function, and behavior. Identifying the stage of ...

Iterative AI-guided optimisation of selective triple-drug combinations for breast cancer

Personalised cancer therapy aims to tailor treatment to individual tumour profiles, yet tumour heterogeneity and adaptive resistance continue to limit...