Latest AI and machine learning research in brain cancer for healthcare professionals.
Ultraviolet (UV) radiation is the primary risk factor for the development of both melanocytic and nonmelanocytic skin cancer. In particular, UVA and UVB radiation are the main cause for DNA damage and inflammatory responses that promote tumor formation, thus, contributing to the development of basal cell carcinoma, squamous cell carcinoma, and melanoma. Furthermore, repeated exposure to UV light a...
INTRODUCTION: Until recently, the widespread use of genetic markers in prostate cancer (PCa) has been limited by the complexities and cost of genomic data analysis. Artificial intelligence (AI), due to its ability to process large volumes of unstructured data, holds the potential to play a transformative role in the future of medical genetics. METHODS: We conducted a systematic literature review u...
The detection of weak radioactive sources in fluctuating background environments is a critical task for nuclear security, environmental monitoring, an...
PURPOSE: To develop and validate a multimodal ensemble machine learning model integrating multi-sequence magnetic resonance imaging (MRI) radiomics, c...
BACKGROUND: Glioblastoma (GBM) is a highly prevalent and aggressive type of brain tumor characterized by profound molecular complexity and poor progno...
Glioblastoma (GBM) continues to be the most lethal form of primary brain tumor. Therapeutic efficacy is significantly hindered by the presence of the ...
PURPOSE: Extranodal extension (ENE) is a biomarker in oropharyngeal carcinoma (OPC) but can only be diagnosed via surgical pathology. We applied an au...
OBJECTIVES: To evaluate the performance of large language models (LLMs) in predicting molecular types of adult-type diffuse gliomas according to the 2...
An increasing number of Artificial intelligence (AI) and machine learning (ML) models are being developed to predict radiation-induced toxicities (RIT...
This study presents BRAIN-META, a reproducible deep learning methodology designed for multi-class brain tumor classification using structural MRI. The...
Accurate segmentation of glioblastoma subregions from multi-parametric MRI is essential for diagnosis, surgical planning, and treatment monitoring in ...
BACKGROUND: Stereotactic Body Radiation Therapy (SBRT) has become an established treatment for several primary and metastatic malignancies; however, c...
PURPOSE: Clinical target volume (CTV) delineation for involved-site radiation therapy (ISRT) in Hodgkin lymphoma (HL) is time-consuming because of the...
The relationship between circadian rhythm disorder and the occurrence and progression of colorectal cancer (CRC) has received attention. The circadian...
PURPOSE: To investigate the efficacy of clinical information, traditional radiological, radiomics and deep-learning features combinations for construc...
Accurate prediction of IDH mutation status in gliomas is critical for guiding diagnosis, prognosis, and treatment planning. We enrolled 2,537 preopera...
OBJECTIVE: Diagnostic reference levels (DRLs) are essential for optimizing radiation dose in CT examinations. However, current DRLs may not reflect th...
PURPOSE: To evaluate whether deep learning reconstruction (DLR) can reduce the radiation dose in routine clinical computed tomography (CT) scans compa...
PURPOSE: Stereotactic radiosurgery (SRS) is a standard treatment for brain metastases; however, it may lead to radiation necrosis (RN). RN can be virt...