Brain Cancer

Metasurface-enhanced terahertz imaging for glioblastoma in orthotopic xenograft mouse model combined with neural network decision making.

Terahertz (THz) optical sensing and imaging offer significant potential in a range of biological and...

Predicting IDH Mutation in Glioma Patients Using Deep Learning Algorithms with Conformal Prediction.

The World Health Organization glioma classification highlights genetic profiles, such as isocitrate ...

Novel Application of Connectomics to the Surgical Management of Pediatric Arteriovenous Malformations.

Introduction The emergence of connectomics in neurosurgery has allowed for construction of detailed ...

Axial Skeletal Assessment in Osteoporosis Using Radiofrequency Echographic Multi-spectrometry: Diagnostic Performance, Clinical Utility, and Future Directions.

Osteoporosis, a prevalent skeletal disorder, necessitates accurate and accessible diagnostic tools f...

Deep learning dosiomics in grade 4 radiation-induced lymphopenia prediction in radiotherapy for esophageal cancer: a multi-center study.

PURPOSE: To investigate the feasibility and accuracy of using deep learning and dosiomics features, ...

Commentary on "radiomics and machine learning model for predicting overall survival in IDH wild-type glioblastoma after gross total resection: a multicenter study".

Artificial intelligence in imaging diagnosis of liver tumors: current status and future prospects.

Liver cancer remains a significant global health concern, ranking as the sixth most common malignanc...

Machine learning-based MRI radiomics predict IL18 expression and overall survival of low-grade glioma patients.

Interleukin-18 has broad immune regulatory functions. Genomic data and enhanced Magnetic Resonance I...

Machine learning model for predicting recurrence following intensity-modulated radiation therapy in nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) exhibits unique histopathological characteristics compare...

Innovative technologies and their clinical prospects for early lung cancer screening.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, due to lack...

A multi-gene predictive model for the radiation sensitivity of nasopharyngeal carcinoma based on machine learning.

Radiotherapy resistance in nasopharyngeal carcinoma (NPC) is a major cause of recurrence and metasta...

Machine learning-based forest fire susceptibility mapping of Southern Mizoram, a part of Indo-Burma Biodiversity Hotspot.

Forest fires are a significant global environmental hazard, causing widespread economic losses and e...

Quasi-supervised MR-CT image conversion based on unpaired data.

. In radiotherapy planning, acquiring both magnetic resonance (MR) and computed tomography (CT) imag...

Nanoneedles enable spatiotemporal lipidomics of living tissues.

Spatial biology provides high-content diagnostic information by mapping the molecular composition of...

Automated feature learning and survival prognostication in grade 4 glioma using supervised machine learning models.

OBJECTIVE: WHO grade 4 glioma is the most common primary malignant brain tumor, with a median surviv...

FFLUNet: Feature Fused Lightweight UNet for brain tumor segmentation.

Brain tumors, particularly glioblastoma multiforme, are considered one of the most threatening types...

Stereotactic Body Radiation Therapy for Primary Renal Cancer and Genetic Markers of Response: A Phase 2 Trial.

Controlled outcome assessment of radiotherapy for primary renal cell carcinoma (RCC) remains limited...

'Bill': An artificial intelligence (AI) clinical scenario coach for medical radiation science education.

INTRODUCTION: The integration of artificial intelligence (AI) into medical radiation science (MRS) e...

Qualitative evaluation of automatic liver segmentation in computed tomography images for clinical use in radiation therapy.

PURPOSE: Segmentation of target volumes and organs at risk on computed tomography (CT) images consti...

Comparative analysis of pre-transcatheter aortic valve implantation CTA protocols: Optimizing radiation dose and contrast volume.

BACKGROUND: To establish the most effective and safe pre-transcatheter aortic valve implantation (TA...

A tumor microenvironment model for glioma diagnosis and therapeutic evaluation based on the analysis of tissues and biological fluids.

Traditional glioma diagnostic methods have limitations, while liquid biopsy is a promising non-invas...