Oncology/Hematology

Brain Cancer

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

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Showing 736-756 of 7,013 articles
Prostatic urinary tract visualization with super-resolution deep learning models.

In urethra-sparing radiation therapy, prostatic urinary tract visualization is important in decreasi...

A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI.

Glioblastoma (GBM) is the most common primary malignant brain tumor in adults. The standard treatmen...

Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity.

OBJECTIVE: In this work, we explore and develop a method that uses Raman spectroscopy to measure and...

Intraoperative cytological diagnosis of brain tumours: A preliminary study using a deep learning model.

BACKGROUND: Intraoperative pathological diagnosis of central nervous system (CNS) tumours is essenti...

The Development of Symbolic Expressions for Fire Detection with Symbolic Classifier Using Sensor Fusion Data.

Fire is usually detected with fire detection systems that are used to sense one or more products res...

DeepEOR: automated perioperative volumetric assessment of variable grade gliomas using deep learning.

PURPOSE: Volumetric assessments, such as extent of resection (EOR) or residual tumor volume, are ess...

Iterative Reconstruction: State-of-the-Art and Future Perspectives.

Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creat...

Fast Near-Field Frequency-Diverse Computational Imaging Based on End-to-End Deep-Learning Network.

The ability to sculpt complex reference waves and probe diverse radiation field patterns have facili...

Radiation therapist perceptions on how artificial intelligence may affect their role and practice.

INTRODUCTION: The use of artificial intelligence (AI) has increased in medical radiation science, wi...

Feasibility of a lung airway navigation system using fiber-Bragg shape sensing and artificial intelligence for early diagnosis of lung cancer.

Currently early diagnosis of malignant lesions at the periphery of lung parenchyma requires guidance...

Ensemble learning for glioma patients overall survival prediction using pre-operative MRIs.

: Gliomas are the most common primary brain tumors. Approximately 70% of the glioma patients diagnos...

Deep learning architecture with transformer and semantic field alignment for voxel-level dose prediction on brain tumors.

PURPOSE: The use of convolution neural networks (CNN) to accurately predict dose distributions can a...

Predicting glioblastoma molecular subtypes and prognosis with a multimodal model integrating convolutional neural network, radiomics, and semantics.

OBJECTIVE: The aim of this study was to build a convolutional neural network (CNN)-based prediction ...

X-ray dose profiles using artificial neural networks.

This paper introduces a novel computational method to simulate and predict radiation dose profiles i...

Computed Tomography of the Spine : Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.

The introduction of the first whole-body CT scanner in 1974 marked the beginning of cross-sectional ...

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