Oncology/Hematology

Brain Cancer

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

7,013 articles
Stay Ahead - Weekly Brain Cancer research updates
Subscribe
Browse Categories
Showing 1198-1218 of 7,013 articles
Microvascularity detection and quantification in glioma: a novel deep-learning-based framework.

Microvascularity is highly correlated with the grading and subtyping of gliomas, making this one of ...

A Deep Learning Model for Predicting Xerostomia Due to Radiation Therapy for Head and Neck Squamous Cell Carcinoma in the RTOG 0522 Clinical Trial.

PURPOSE: Xerostomia commonly occurs in patients who undergo head and neck radiation therapy and can ...

Markerless Pancreatic Tumor Target Localization Enabled By Deep Learning.

PURPOSE: Deep learning is an emerging technique that allows us to capture imaging information beyond...

DRRNet: Dense Residual Refine Networks for Automatic Brain Tumor Segmentation.

Glioma is one of the most common and aggressive brain tumors. Segmentation and subsequent quantitati...

Applications and limitations of machine learning in radiation oncology.

Machine learning approaches to problem-solving are growing rapidly within healthcare, and radiation ...

Development and Validation of a Bayesian Network Method to Detect External Beam Radiation Therapy Physician Order Errors.

PURPOSE: To investigate a Bayesian network (BN)-based method to detect errors in external beam radia...

GRUU-Net: Integrated convolutional and gated recurrent neural network for cell segmentation.

Cell segmentation in microscopy images is a common and challenging task. In recent years, deep neura...

Automated brain histology classification using machine learning.

Brain and breast tumors cause significant morbidity and mortality worldwide. Accurate and expedient ...

Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction.

Solar energy is a major type of renewable energy, and its estimation is important for decision-maker...

Glioma stages prediction based on machine learning algorithm combined with protein-protein interaction networks.

BACKGROUND: Glioma is the most lethal nervous system cancer. Recent studies have made great efforts ...

ONCOhabitats: A system for glioblastoma heterogeneity assessment through MRI.

BACKGROUND: Neuroimaging analysis is currently crucial for an early assessment of glioblastoma, to h...

Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI.

PURPOSE: To predict the neoadjuvant chemoradiation therapy (CRT) response in patients with locally a...

Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm.

Recent analysis identified distinct genomic subtypes of lower-grade glioma tumors which are associat...

A deep learning radiomics model for preoperative grading in meningioma.

OBJECTIVES: To noninvasively differentiate meningioma grades by deep learning radiomics (DLR) model ...

Multimodal brain tumor image segmentation using WRN-PPNet.

Tumor segmentation is of great importance for diagnosis and prognosis of brain cancer in medical fie...

Attention-aware fully convolutional neural network with convolutional long short-term memory network for ultrasound-based motion tracking.

PURPOSE: One of the promising options for motion management in radiation therapy (RT) is the use of ...

Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.

BACKGROUND: This study aimed to examine multi-dimensional MRI features' predictability on survival o...

Browse Categories