Brain Cancer

Unlocking the Power of ChatGPT, Artificial Intelligence, and Large Language Models: Practical Suggestions for Radiation Oncologists.

Recent advances in artificial intelligence (AI), such as generative AI and large language models (LL...

Circulating Plasma Exosomal PD-L1 Predicts Prognosis of Head and Neck Squamous Cell Carcinoma After Radiation Therapy.

PURPOSE: Radiation therapy is widely used to treat head and neck squamous cell carcinoma (HNSCC). Th...

Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis.

BACKGROUND: Meningiomas are common intracranial tumors. Machine learning (ML) algorithms are emergin...

Preoperative Discrimination of CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytoma: A Deep Learning-Based Radiomics Model Using MRI.

BACKGROUND: Cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion has been verified ...

Deep learning-based scan range optimization can reduce radiation exposure in coronary CT angiography.

OBJECTIVES: Cardiac computed tomography (CT) is essential in diagnosing coronary heart disease. Howe...

A novel MRI-based deep learning networks combined with attention mechanism for predicting CDKN2A/B homozygous deletion status in IDH-mutant astrocytoma.

OBJECTIVES: To develop a high-accuracy MRI-based deep learning method for predicting cyclin-dependen...

Suitability of DNN-based vessel segmentation for SIRT planning.

PURPOSE: The segmentation of the hepatic arteries (HA) is essential for state-of-the-art pre-interve...

Amplifying the Effects of Contrast Agents on Magnetic Resonance Images Using a Deep Learning Method Trained on Synthetic Data.

OBJECTIVES: Artificial intelligence (AI) methods can be applied to enhance contrast in diagnostic im...

Submillimeter Multifunctional Ferromagnetic Fiber Robots for Navigation, Sensing, and Modulation.

Small-scale robots capable of remote active steering and navigation offer great potential for biomed...

Ultra-low-dose computed tomography with deep learning reconstruction for craniosynostosis at radiation doses comparable to skull radiographs: a pilot study.

BACKGROUND: Craniofacial computed tomography (CT) is the diagnostic investigation of choice for cran...

An AI Predictive Model to Determine Who Benefits from ADT with Radiation: Working Smarter, Not Harder.

Whether you are a surgical, medical, or radiation oncologist, the care goals remain the same, that i...

A deep-learning assisted bioluminescence tomography method to enable radiation targeting in rat glioblastoma.

. A novel solution is required for accurate 3D bioluminescence tomography (BLT) based glioblastoma (...

Auto-Segmentation and Classification of Glioma Tumors with the Goals of Treatment Response Assessment Using Deep Learning Based on Magnetic Resonance Imaging.

Glioma is the most common primary intracranial neoplasm in adults. Radiotherapy is a treatment appro...

Response to "Large language model artificial intelligence: the current state and future of ChatGPT in neuro-oncology publishing".

Machine learning to predict environmental dose rates from a radionuclide therapy service - a proof of concept study.

The Ionising Radiation Regulations 2017 requires prior risk assessment calculations and regular envi...

Artificial Intelligence Predictive Model for Hormone Therapy Use in Prostate Cancer.

BACKGROUND: Androgen deprivation therapy (ADT) with radiotherapy can benefit patients with localized...

Deep learning-based body weight from scout images can be an alternative to actual body weight in CT radiation dose management.

PURPOSE: Accurate body weight measurement is essential to promote computed tomography (CT) dose opti...

Automated deep learning auto-segmentation of air volumes for MRI-guided online adaptive radiation therapy of abdominal tumors.

. In the current MR-Linac online adaptive workflow, air regions on the MR images need to be manually...

Editorial for "Preoperative Discrimination of CDKN2A/B Homozygous Deletion Status in Isocitrate Dehydrogenase-Mutant Astrocytoma: A Deep Learning-Based Radiomics Model Using MRI".

Deep learning-assisted radiomics facilitates multimodal prognostication for personalized treatment strategies in low-grade glioma.

Determining the optimal course of treatment for low grade glioma (LGG) patients is challenging and f...

Is There a Role for Machine Learning in Liquid Biopsy for Brain Tumors? A Systematic Review.

The paucity of studies available in the literature on brain tumors demonstrates that liquid biopsy (...