Brain Cancer

Radiation pneumonitis prediction after stereotactic body radiation therapy based on 3D dose distribution: dosiomics and/or deep learning-based radiomics features.

BACKGROUND: This study was designed to establish radiation pneumonitis (RP) prediction models using ...

Radiation Dosimetry, Artificial Intelligence and Digital Twins: Old Dog, New Tricks.

Developments in artificial intelligence, particularly convolutional neural networks and deep learnin...

Assessment of Thermal Damage from Robot-Drilled Craniotomy for Cranial Window Surgery in Mice.

Cranial window surgery allows for the imaging of brain tissue in live mice with the use of multiphot...

Shuffle-ResNet: Deep learning for predicting LGG IDH1 mutation from multicenter anatomical MRI sequences.

The world health organization recommended to incorporate gene information such as isocitrate dehydro...

Deep reinforcement learning and its applications in medical imaging and radiation therapy: a survey.

Reinforcement learning takes sequential decision-making approaches by learning the policy through tr...

Brain tumor classification based on neural architecture search.

Brain tumor is a life-threatening disease and causes about 0.25 million deaths worldwide in 2020. Ma...

Deep learning characterization of brain tumours with diffusion weighted imaging.

Glioblastoma multiforme (GBM) is one of the most deadly forms of cancer. Methods of characterizing t...

Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.

BACKGROUND: Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear accelerato...

Overcoming challenges of translating deep-learning models for glioblastoma: the ZGBM consortium.

OBJECTIVE: To report imaging protocol and scheduling variance in routine care of glioblastoma patien...

Revealing low-temperature plasma efficacy through a dose-rate assessment by DNA damage detection combined with machine learning models.

Low-temperature plasmas have quickly emerged as alternative and unconventional types of radiation th...

Emergence of MXene and MXene-Polymer Hybrid Membranes as Future- Environmental Remediation Strategies.

The continuous deterioration of the environment due to extensive industrialization and urbanization ...

Predicting Meningioma Resection Status: Use of Deep Learning.

Fast Deformable Image Registration for Real-Time Target Tracking During Radiation Therapy Using Cine MRI and Deep Learning.

PURPOSE: We developed a deep learning (DL) model for fast deformable image registration using 2-dime...

Clinical target volume segmentation based on gross tumor volume using deep learning for head and neck cancer treatment.

Accurate clinical target volume (CTV) delineation is important for head and neck intensity-modulated...

Input feature design and its impact on the performance of deep learning models for predicting fluence maps in intensity-modulated radiation therapy.

. Deep learning (DL) models for fluence map prediction (FMP) have great potential to reduce treatmen...

Clinical applicability of deep learning-based respiratory signal prediction models for four-dimensional radiation therapy.

For accurate respiration gated radiation therapy, compensation for the beam latency of the beam cont...

Low SNR Multi-Emitter Signal Sorting and Recognition Method Based on Low-Order Cyclic Statistics CWD Time-Frequency Images and the YOLOv5 Deep Learning Model.

It is difficult for traditional signal-recognition methods to effectively classify and identify mult...

Exploration of biomedical knowledge for recurrent glioblastoma using natural language processing deep learning models.

BACKGROUND: Efficient exploration of knowledge for the treatment of recurrent glioblastoma (GBM) is ...

Deep learning algorithm reveals two prognostic subtypes in patients with gliomas.

BACKGROUND: Gliomas are highly complex and heterogeneous tumors, rendering prognosis prediction chal...

A hierarchical machine learning model based on Glioblastoma patients' clinical, biomedical, and image data to analyze their treatment plans.

AIM OF STUDY: Glioblastoma Multiforme (GBM) is an aggressive brain cancer in adults that kills most ...

Implementation of machine learning in the clinic: challenges and lessons in prospective deployment from the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) randomized controlled study.

BACKGROUND: Artificial intelligence (AI) and machine learning (ML) have resulted in significant enth...