Oncology/Hematology

Brain Cancer

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

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Value of artificial intelligence in neuro-oncology.

CNS cancers are complex, difficult-to-treat malignancies that remain insufficiently understood and m...

Novel radiotherapy target definition using AI-driven predictions of glioblastoma recurrence from metabolic and diffusion MRI.

The current standard-of-care (SOC) practice for defining the clinical target volume (CTV) for radiat...

Phenotype augmentation using generative AI for isocitrate dehydrogenase mutation prediction in glioma.

This study investigated the effects of feature augmentation, which uses generated images with specif...

Machine learning on multiple epigenetic features reveals H3K27Ac as a driver of gene expression prediction across patients with glioblastoma.

Epigenetic mechanisms play a crucial role in driving transcript expression and shaping the phenotypi...

Machine learning and deep learning in glioblastoma: a systematic review and meta-analysis of diagnosis, prognosis, and treatment.

INTRODUCTION: Glioblastoma (GBM) is the most malignant primary brain cancer, associated with a media...

Advances in renal cancer: diagnosis, treatment, and emerging technologies.

This review provides a comprehensive overview of current practices and recent advancements in the di...

A brain tumor segmentation enhancement in MRI images using U-Net and transfer learning.

This paper presents a novel transfer learning approach for segmenting brain tumors in Magnetic Reson...

Large language models for extraction of OPS-codes from operative reports in meningioma surgery.

BACKGROUND: In the German medical billing system, surgical departments encode their procedures in OP...

Deep learning-based real-time detection of head and neck tumors during radiation therapy.

Clinical drivers for real-time head and neck (H&N) tumor tracking during radiation therapy (RT) are ...

Radiation enteritis associated with temporal sequencing of total neoadjuvant therapy in locally advanced rectal cancer: a preliminary study.

BACKGROUND: This study aimed to develop and validate a multi-temporal magnetic resonance imaging (MR...

A deep learning model for predicting radiation-induced xerostomia in patients with head and neck cancer based on multi-channel fusion.

OBJECTIVES: Radiation-induced xerostomia is a common sequela in patients who undergo head and neck r...

High-Resolution Ultrasound Data for AI-Based Segmentation in Mouse Brain Tumor.

Glioblastoma multiforme (GBM) is the most aggressive type of brain cancer, making effective treatmen...

Classification of Brain Tumors in MRI Images with Brain-CNXSAMNet: Integrating Hybrid ConvNeXt and Spatial Attention Module Networks.

Brain tumors (BT) can cause fatal outcomes by affecting body functions, making precise early detecti...

Time-series X-ray image prediction of dental skeleton treatment progress via neural networks.

Accurate prediction of skeletal changes during orthodontic treatment in growing patients remains cha...

Prediction of MGMT methylation status in glioblastoma patients based on radiomics feature extracted from intratumoral and peritumoral MRI imaging.

Assessing MGMT promoter methylation is crucial for determining appropriate glioblastoma therapy. Pre...

Prediction of 1p/19q state in glioma by integrated deep learning method based on MRI radiomics.

PURPOSE: To predict the 1p/19q molecular status of Lower-grade glioma (LGG) patients nondestructivel...

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