Oncology/Hematology

Brain Cancer

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

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Showing 337-357 of 6,990 articles
Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations.

BACKGROUND: Accurate calculation of lung cancer dose using the Monte Carlo (MC) algorithm in CyberKn...

CT ventilation images produced by a 3D neural network show improvement over the Jacobian and HU DIR-based methods to predict quantized lung function.

BACKGROUND: Radiation-induced pneumonitis affects up to 33% of non-small cell lung cancer (NSCLC) pa...

Decoding Glioblastoma Heterogeneity: Neuroimaging Meets Machine Learning.

Recent advancements in neuroimaging and machine learning have significantly improved our ability to ...

Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning.

This study aims to investigate the feasibility of utilizing generative adversarial networks (GANs) t...

Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.

Brain metastases (BMs) in extensive-stage small cell lung cancer (ES-SCLC) are often associated with...

Evaluating ChatGPT's competency in radiation oncology: A comprehensive assessment across clinical scenarios.

PURPOSE: Artificial intelligence (AI) and machine learning present an opportunity to enhance clinica...

Application of Artificial Intelligence in Prediction of Ki-67 Index in Meningiomas: A Systematic Review and Meta-Analysis.

BACKGROUND: The Ki-67 index is a histopathological marker that has been reported to be a crucial fac...

Attention 3D UNET for dose distribution prediction of high-dose-rate brachytherapy of cervical cancer: Intracavitary applicators.

BACKGROUND: Formulating a clinically acceptable plan within the time-constrained clinical setting of...

Artificial intelligence neural network and fuzzy modelling of unsteady Sisko trihybrid nanofluids for cancer therapy with entropy insights.

The main objective of the current endeavor is to monitor hypothetical processes utilizing a Sisko tr...

AI tool for predicting MGMT methylation in glioblastoma for clinical decision support in resource limited settings.

Glioblastoma is an aggressive brain cancer with a poor prognosis. The O6-methylguanine-DNA methyltra...

Feasibility of Ultra-low Radiation and Contrast Medium Dosage in Aortic CTA Using Deep Learning Reconstruction at 60 kVp: An Image Quality Assessment.

OBJECTIVE: To assess the viability of using ultra-low radiation and contrast medium (CM) dosage in a...

Machine learning model reveals the role of angiogenesis and EMT genes in glioma patient prognosis and immunotherapy.

Gliomas represent a highly aggressive class of tumors located in the brain. Despite the availability...

Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches.

Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-relate...

Automatic delineation of cervical cancer target volumes in small samples based on multi-decoder and semi-supervised learning and clinical application.

Radiotherapy has been demonstrated to be one of the most significant treatments for cervical cancer,...

Evaluating the Efficacy of Deep Learning Reconstruction in Reducing Radiation Dose for Computer-Aided Volumetry for Liver Tumor: A Phantom Study.

OBJECTIVE: The purpose of this study was to compare radiation dose reduction capability for accurate...

Human-Artificial Intelligence Symbiotic Reporting for Theranostic Cancer Care.

Reporting of diagnostic nuclear images in clinical cancer management is generally qualitative. Thera...

Convolutional neural network-based classification of craniosynostosis and suture lines from multi-view cranial X-rays.

Early and precise diagnosis of craniosynostosis (CSO), which involves premature fusion of cranial su...

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