Latest AI and machine learning research in brain cancer for healthcare professionals.
EGFR amplification occurs in approximately 40-50% of glioblastoma (GBM) cases and is critical for treatment selection [1]. However, GBM tissue samples frequently yield insufficient material for comprehensive molecular testing due to extensive necrosis and tissue quality limitations [2]. This affects thousands of patients annually in the United States [4]. We developed a microenvironment-inferred g...
This work introduces a novel and specialized dataset of high-resolution fluorescence microscopic images focused on astrocytic gap junctions, aiming to get insights into intercellular communication in both healthy and pathological brain conditions. The dataset includes 20 z-stack image series—10 from human glioblastoma tissue and 10 from healthy rat brain tissue—each containing between 22 and 104 o...
Multi-omics integrative analysis is pivotal for elucidating complex molecular mechanisms and biological processes, yet remains challenging in multi-om...
Chronic diseases often require repeated oral or local administration, which can compromise patient compliance. In wet age-related macular degeneration...
In this study, we present a comprehensive radiogenomic analysis of pediatric low-grade gliomas (pLGGs), combining treatment-naïve multiparametric MRI ...
Large language models (LLMs) like ChatGPT showed great potential in aiding medical research. A heavy workload in filtering records is needed during th...
Given the high prevalence of vertebral fractures post-radiotherapy in patients with metastatic spine disease, accurate and rapid muscle segmentation c...
To assess the rate of retinal vascularisation derived from ultra-widefield (UWF) imaging-based retinopathy of prematurity (ROP) screening as predictor...
While mammography is commonly used for breast cancer detection, its widespread implementation in resource-constrained nations is challenging. Artifici...
Magnetic resonance images (MRI) of the brain exhibit high dimensionality that pose significant challenges for computational analysis. While models pro...
Artificial intelligence (AI) foundation models such as Segment Anything Model 2 (SAM 2) offer potential for semi-automated image segmentation with min...
To evaluate the potential of wrist-worn wearable devices to detect and quantify Faciobrachial Dystonic Seizures (FBDS) and related events associated w...
A comprehensive analysis of artificial intelligence’s (AI) integration into neurosurgery is vital to identify research priorities, address gaps, and i...
Large language models (LLMs) have demonstrated advanced capabilities in interpreting text and visual inputs. Their potential to transform oncological ...
In this study, we develop and validate an interpretable machine learning (ML) model that integrates a hybrid Swarm Intelligence (SI)–based feature sel...
The molecular profiling of gliomas for isocitrate dehydrogenase (IDH) mutations currently relies on resected tumor samples, highlighting the need for ...
In glioblastoma (GBM), promoter methylation of the O6-methylguanine-DNA methyltransferase (MGMT) is associated with beneficial chemotherapy but has no...
The quantification of the Ki-67 labeling index (LI) is critical for assessing tumor proliferation and prognosis in tumors, yet manual scoring remains ...
Late radiation-associated dysphagia after head and neck cancer (HNC) significantly impacts patient’s health and quality of life. Conventional normal t...
Glaucoma is increasingly recognized as a neurodegenerative condition involving both retinal and central nervous system structures. Here, we present an...