Brain Cancer

Deep-Learning Model Prediction of Radiation Pneumonitis Using Pretreatment Chest Computed Tomography and Clinical Factors.

This study aimed to build a comprehensive deep-learning model for the prediction of radiation pneum...

CNN-based glioma detection in MRI: A deep learning approach.

BACKGROUND: More than a million people are affected by brain tumors each year; high-grade gliomas (H...

Artificial Intelligence Application for Anti-tumor Drug Synergy Prediction.

Currently, the main therapeutic methods for cancer include surgery, radiation therapy, and chemother...

Meta-transfer Learning for Brain Tumor Segmentation: Within and Beyond Glioma.

In recent years, numerous algorithms have emerged for the segmentation of brain tumors, propelled by...

Machine Learning and Radiomics in Gliomas.

The integration of machine learning (ML) and radiomics is emerging as a pivotal advancement in gliom...

Machine and Deep Learning in Hyperspectral Fluorescence-Guided Brain Tumor Surgery.

Malignant glioma resection is often the first line of treatment in neuro-oncology. During glioma sur...

Computational Modeling and AI in Radiation Neuro-Oncology and Radiosurgery.

The chapter explores the extensive integration of artificial intelligence (AI) in healthcare systems...

Enhancing coronary artery plaque analysis via artificial intelligence-driven cardiovascular computed tomography.

Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality of cardiac structu...

Response to "Medical Statistics Unlock the Gateway to Further Research: Using Deep Learning to Predict CDKN2A/B Homozygous Deletion in Isocitrate Dehydrogenase-Mutant Astrocytoma".

Medical Statistics Unlock the Gateway to Further Research: Using Deep Learning to Predict CDKN2A/B Homozygous Deletion in Isocitrate Dehydrogenase-Mutant Astrocytoma.

[Robot-assisted prostatectomy for PT3. Oncological and functional outcomes].

In 2020, prostate cancer (PCa) ranked third in the structure of the most significant oncological dis...

[Research Progress in the Application of Ultrasound-Guided Robot in Minimally Invasive Surgery].

With the continuous advances in modern medical technology and equipment,minimally invasive surgery (...

Evaluation of deep learning-based deliverable VMAT plan generated by prototype software for automated planning for prostate cancer patients.

This study aims to evaluate the dosimetric accuracy of a deep learning (DL)-based deliverable volume...

Impact of a reduced iodine load with deep learning reconstruction on abdominal MDCT.

To evaluate the impact of a reduced iodine load using deep learning reconstruction (DLR) on the hepa...

[A Dual-Aware deep learning framework for identification of glioma isocitrate dehydrogenase genotype using magnetic resonance amide proton transfer modalities].

OBJECTIVE: To propose a Dual-Aware deep learning framework for genotyping of isocitrate dehydrogenas...

Unlocking glioma genetics with deep learning.

The AI era in medicine has ushered in new opportunities to improve the diagnosis and treatment of hu...

Development of a deep learning-based error detection system without error dose maps in the patient-specific quality assurance of volumetric modulated arc therapy.

To detect errors in patient-specific quality assurance (QA) for volumetric modulated arc therapy (VM...

Deep learning based on preoperative magnetic resonance (MR) images improves the predictive power of survival models in primary spinal cord astrocytomas.

BACKGROUND: Prognostic models for spinal cord astrocytoma patients are lacking due to the low incide...

Integrative Imaging Informatics for Cancer Research: Workflow Automation for Neuro-Oncology (I3CR-WANO).

PURPOSE: Efforts to use growing volumes of clinical imaging data to generate tumor evaluations conti...

Code-free machine learning for classification of central nervous system histopathology images.

Machine learning (ML), an application of artificial intelligence, is currently transforming the anal...

Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning.

BACKGROUND: Accurate characterization of glioma is crucial for clinical decision making. A delineati...