Oncology/Hematology

Brain Cancer

Latest AI and machine learning research in brain cancer for healthcare professionals.

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Agentic Automation of BT-RADS Scoring: End-to-End Multi-Agent System for Standardized Brain Tumor Follow-up Assessment

The Brain Tumor Reporting and Data System (BT-RADS) standardizes post-treatment MRI response assessm...

Enhancing Brain Tumor Classification Using Vision Transformers with Colormap-Based Feature Representation on BRISC2025 Dataset

Accurate classification of brain tumors from magnetic resonance imaging (MRI) plays a critical role ...

Cross-Modal Training Using Xenium Spatial Transcriptomics Enables DINO-DETR Based Detection of Vascular Niches in H&E Whole-Slide Images

Background: Tumor vasculature is a key driver of glioma progression, yet routine quantification depe...

SA-CycleGAN-2.5D: Self-Attention CycleGAN with Tri-Planar Context for Multi-Site MRI Harmonization

Multi-site neuroimaging analysis is fundamentally confounded by scanner-induced covariate shifts, wh...

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 uncon...

Multimodal classification of Radiation-Induced Contrast Enhancements and tumor recurrence using deep learning

The differentiation between tumor recurrence and radiation-induced contrast enhancements in post-tre...

SpatioCAD: Context-aware graph diffusion model for pinpointing spatially variable genes in heterogeneous tissues

Spatial transcriptomics enables comprehensive characterization of tissue architecture, and the ident...

Rectified flow-based prediction of post-treatment brain MRI from pre-radiotherapy priors for patients with glioma

Purpose/Objective: Brain tumors result in 20 years of lost life on average. Standard therapies induc...

Brain-WM: Brain Glioblastoma World Model

Precise prognostic modeling of glioblastoma (GBM) under varying treatment interventions is essential...

AI End-to-End Radiation Treatment Planning Under One Second

Artificial intelligence-based radiation therapy (RT) planning has the potential to reduce planning t...

OncoRAG: Graph-Based Retrieval Enabling Clinical Phenotyping from Oncology Notes Using Local Mid-Size Language Models

Introduction: Manual data extraction from unstructured clinical notes is labor-intensive and impract...

Comparative Evaluation of Traditional Methods and Deep Learning for Brain Glioma Imaging. Review Paper

Segmentation is crucial for brain gliomas as it delineates the glioma s extent and location, aiding ...

TumorFlow: Physics-Guided Longitudinal MRI Synthesis of Glioblastoma Growth

Glioblastoma exhibits diverse, infiltrative, and patient-specific growth patterns that are only part...

CoRe-BT: A Multimodal Radiology-Pathology-Text Benchmark for Robust Brain Tumor Typing

Accurate brain tumor typing requires integrating heterogeneous clinical evidence, including magnetic...

TumorFlow: Physics-Guided Longitudinal MRI Synthesis of Glioblastoma Growth

Glioblastoma exhibits diverse, infiltrative, and patient-specific growth patterns that are only part...

h5adify: neuro-symbolic metadata harmonizationenables scalable AnnData integration with locallarge language models

Background: The rapid growth of public single-cell and spatial transcriptomics repositories has shif...

Temporal dynamics of radiotherapy and chemotherapy response in lower-grade gliomas using causal machine learning

Lower-grade gliomas (World Health Organization [WHO] grades 2-3) exhibit variable treatment response...

Detecting Extrachromosomal DNA from Routine Histopathology

Extrachromosomal DNA (ecDNA) is a major driver of oncogene amplification, tumour heterogeneity and p...

Act or Defer: Error-Controlled Decision Policies for Medical Foundation Models

Clinical deployment of foundation models requires decision policies that operate under explicit erro...

Morphological set enrichment enables interpretable prognostication and molecular profiling of meningiomas

Meningiomas are the most common primary brain tumors and, despite their benign reputation, often beh...

XMorph: Explainable Brain Tumor Analysis Via LLM-Assisted Hybrid Deep Intelligence

Deep learning has significantly advanced automated brain tumor diagnosis, yet clinical adoption rema...

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