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 946-966 of 7,013 articles
Technical Note: Dose prediction for radiation therapy using feature-based losses and One Cycle Learning.

PURPOSE: To present the technical details of the runner-up model in the open knowledge-based plannin...

Robot assisted laser-interstitial thermal therapy with iSYS1 and Visualase: how I do it.

BACKGROUND: Laser-interstitial thermal therapy (LITT) is an ablative treatment based on a surgically...

Performance evaluation of a deep learning image reconstruction (DLIR) algorithm in "double low" chest CTA in children: a feasibility study.

BACKGROUND: Chest CT angiography (CTA) is a convenient clinical examination for children with an inc...

Semi-Supervised Deep Learning-Based Image Registration Method with Volume Penalty for Real-Time Breast Tumor Bed Localization.

Breast-conserving surgery requires supportive radiotherapy to prevent cancer recurrence. However, th...

Potential and limitations of radiomics in neuro-oncology.

Radiomics seeks to apply classical methods of image processing to obtain quantitative parameters fro...

Predicting cell behaviour parameters from glioblastoma on a chip images. A deep learning approach.

The broad possibilities offered by microfluidic devices in relation to massive data monitoring and a...

Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer.

Machine learning (ML) holds great promise for impacting healthcare delivery; however, to date most m...

An assessment of contamination pickup on ground robotic vehicles for nuclear surveying application.

Ground robotic vehicles are often deployed to inspect areas where radioactive floor contamination is...

Joint Detection of Tap and CEA Based on Deep Learning Medical Image Segmentation: Risk Prediction of Thyroid Cancer.

In recent years, the incidence of thyroid nodules has shown an increasing trend year by year and has...

Machine learning based differentiation of glioblastoma from brain metastasis using MRI derived radiomics.

Few studies have addressed radiomics based differentiation of Glioblastoma (GBM) and intracranial me...

Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care.

In a time of rapid advances in science and technology, the opportunities for radiation oncology are ...

Knowledge-infused Global-Local Data Fusion for Spatial Predictive Modeling in Precision Medicine.

The automated capability of generating spatial prediction for a variable of interest is desirable in...

Machine learning applications to neuroimaging for glioma detection and classification: An artificial intelligence augmented systematic review.

Glioma is the most common primary intraparenchymal tumor of the brain and the 5-year survival rate o...

Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: A critical review.

Advances in artificial intelligence-based methods have led to the development and publication of num...

Radiomics-based neural network predicts recurrence patterns in glioblastoma using dynamic susceptibility contrast-enhanced MRI.

Glioblastoma remains the most devastating brain tumor despite optimal treatment, because of the high...

Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance.

Resistance to ionizing radiation, a first-line therapy for many cancers, is a major clinical challen...

Generative adversarial network for glioblastoma ensures morphologic variations and improves diagnostic model for isocitrate dehydrogenase mutant type.

Generative adversarial network (GAN) creates synthetic images to increase data quantity, but whether...

A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy.

BACKGROUND AND PURPOSE: Delineating organs at risk (OARs) on computed tomography (CT) images is an e...

Browse Categories