AIMC Topic: Glioma
Clear Filters Showing 51 to 60 of 387 articles
Can we rely on machine learning algorithms as a trustworthy predictor for recurrence in high-grade glioma? A systematic review and meta-analysis.
Clinical neurology and neurosurgery
Jan 25, 2025
Early prediction of recurrence in high-grade glioma (HGG) is critical due to its aggressive nature and poor prognosis. Distinguishing true recurrence from treatment-related changes, such as radionecrosis, is a major diagnostic challenge. Machine lear...
An interpretable multi-scale convolutional attention residual neural network for glioma grading with Raman spectroscopy.
Analytical methods : advancing methods and applications
Jan 23, 2025
Since the malignancy of gliomas varies with their grade, classifying gliomas of different grades can assist doctors in developing personalized surgical plans during surgery, thereby improving the prognosis. Raman spectroscopy is an optical method for...
Comparative analysis of deep learning and radiomic signatures for overall survival prediction in recurrent high-grade glioma treated with immunotherapy.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jan 21, 2025
BACKGROUND: Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-consuming and poses significa...
Clinical impact of an explainable machine learning with amino acid PET imaging: application to the diagnosis of aggressive glioma.
European journal of nuclear medicine and molecular imaging
Jan 17, 2025
PURPOSE: Radiomics-based machine learning (ML) models of amino acid positron emission tomography (PET) images have shown efficiency in glioma prediction tasks. However, their clinical impact on physician interpretation remains limited. This study inv...
A hybrid explainable model based on advanced machine learning and deep learning models for classifying brain tumors using MRI images.
Scientific reports
Jan 10, 2025
Brain tumors present a significant global health challenge, and their early detection and accurate classification are crucial for effective treatment strategies. This study presents a novel approach combining a lightweight parallel depthwise separabl...
Diagnostic Accuracy of Ambient Mass Spectrometry with Blood Plasma in a Murine Glioma Model Using Machine Learning.
World neurosurgery
Jan 9, 2025
OBJECTIVE: Malignant glioma progresses rapidly and shows poor prognosis, but clinically applicable blood plasma-based biochemical tumor markers remain lacking. This study aimed to develop a diagnostic system using probe electrospray ionization mass s...
Deep learning-integrated MRI brain tumor analysis: feature extraction, segmentation, and Survival Prediction using Replicator and volumetric networks.
Scientific reports
Jan 9, 2025
The most prevalent form of malignant tumors that originate in the brain are known as gliomas. In order to diagnose, treat, and identify risk factors, it is crucial to have precise and resilient segmentation of the tumors, along with an estimation of ...
Impact of glioma metabolism-related gene ALPK1 on tumor immune heterogeneity and the regulation of the TGF-β pathway.
Frontiers in immunology
Jan 7, 2025
BACKGROUND: Recent years have seen persistently poor prognoses for glioma patients. Therefore, exploring the molecular subtyping of gliomas, identifying novel prognostic biomarkers, and understanding the characteristics of their immune microenvironme...
Dual-path neural network extracts tumor microenvironment information from whole slide images to predict molecular typing and prognosis of Glioma.
Computer methods and programs in biomedicine
Jan 4, 2025
BACKGROUND AND OBJECTIVE: Utilizing AI to mine tumor microenvironment information in whole slide images (WSIs) for glioma molecular subtype and prognosis prediction is significant for treatment. Existing weakly-supervised learning frameworks based on...
Weakly supervised deep learning-based classification for histopathology of gliomas: a single center experience.
Scientific reports
Jan 2, 2025
Multiple artificial intelligence systems have been created to facilitate accurate and prompt histopathological diagnosis of tumors using hematoxylin-eosin-stained slides. We aimed to investigate whether weakly supervised deep learning can aid in glio...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32021
- Neural Networks, Computer 30231
- Algorithms 27405
- Deep Learning 26912
- Artificial Intelligence 24844
- Robotics 13389
- Image Processing, Computer-Assisted 9738
- Retrospective Studies 9346
- Magnetic Resonance Imaging 6347
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4866
- Support Vector Machine 4771
- Computational Biology 4333
- Brain 4129
- Computer Simulation 3935
Recent Journals
- Scientific reports 6800
- Sensors (Basel, Switzerland) 4794
- PloS one 4210
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1172
- Journal of chemical information and modeling 1066
- Nature communications 1047
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 874
- Journal of medical Internet research 864
- Briefings in bioinformatics 853