Oncology/Hematology

Brain Cancer

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

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Showing 295-315 of 6,990 articles
Development and external validation of a multi-task feature fusion network for CTV segmentation in cervical cancer radiotherapy.

BACKGROUND AND PURPOSE: Accurate segmentation of the clinical target volume (CTV) is essential to de...

Survival prediction of glioblastoma patients using machine learning and deep learning: a systematic review.

Glioblastoma Multiforme (GBM), classified as a grade IV glioma by the World Health Organization (WHO...

Descriptive overview of AI applications in x-ray imaging and radiotherapy.

Artificial intelligence (AI) is transforming medical radiation applications by handling complex data...

Recent Advances and Future Directions in Sonodynamic Therapy for Cancer Treatment.

Deep-tissue solid cancer treatment has a poor prognosis, resulting in a very low 5-year patient surv...

Radiomics and deep learning models for glioblastoma treatment outcome prediction based on tumor invasion modeling.

PURPOSE: We investigate the feasibility of using a biophysically guided approach for delineating the...

A unified deep-learning framework for enhanced patient-specific quality assurance of intensity-modulated radiation therapy plans.

BACKGROUND: Modern radiation therapy techniques, such as intensity-modulated radiation therapy (IMRT...

Ensemble learning-based radiomics model for discriminating brain metastasis from glioblastoma.

OBJECTIVE: Differentiating between brain metastasis (BM) and glioblastoma (GBM) preoperatively is ch...

Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).

To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning sy...

Automated Measurement of Effective Radiation Dose by F-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography.

BACKGROUND/OBJECTIVES: Calculating the radiation dose from CT in F-PET/CT examinations poses a signi...

VASARI 2.0: a new updated MRI VASARI lexicon to predict grading and status in brain glioma.

INTRODUCTION: Precision medicine refers to managing brain tumors according to each patient's unique ...

CXCL12 impact on glioblastoma cells behaviors under dynamic culture conditions: Insights for developing new therapeutic approaches.

Glioblastoma multiforme (GBM) is the most prevalent malignant brain tumor, with an average survival ...

Improving prediction of solar radiation using Cheetah Optimizer and Random Forest.

In the contemporary context of a burgeoning energy crisis, the accurate and dependable prediction of...

Artificial Intelligence-Empowered Multistep Integrated Radiation Therapy Workflow for Nasopharyngeal Carcinoma.

PURPOSE: To establish an artificial intelligence (AI)-empowered multistep integrated (MSI) radiation...

Deep learning radiomics nomograms predict Isocitrate dehydrogenase (IDH) genotypes in brain glioma: A multicenter study.

PURPOSE: To explore the feasibility of Deep learning radiomics nomograms (DLRN) in predicting IDH ge...

Personalized deep learning auto-segmentation models for adaptive fractionated magnetic resonance-guided radiation therapy of the abdomen.

BACKGROUND: Manual contour corrections during fractionated magnetic resonance (MR)-guided radiothera...

Generating 3D brain tumor regions in MRI using vector-quantization Generative Adversarial Networks.

Medical image analysis has significantly benefited from advancements in deep learning, particularly ...

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