A comprehensive review on machine learning in brain tumor classification: taxonomy, challenges, and future trends
Abstract In recent years, Machine Learning (ML), a key component of artificial intelligence
(AI), has become increasingly popular in data analysis and processing. ML is now widely …
(AI), has become increasingly popular in data analysis and processing. ML is now widely …
[HTML][HTML] Recent Applications of Explainable AI (XAI): A Systematic Literature Review
This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …
Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysis
L Li, F **ao, S Wang, S Kuang, Z Li, Y Zhong, D Xu… - Scientific Reports, 2024 - nature.com
Abstract O6-methylguanine-DNA methyltransferase (MGMT) has been demonstrated to be
an important prognostic and predictive marker in glioblastoma (GBM). To establish a reliable …
an important prognostic and predictive marker in glioblastoma (GBM). To establish a reliable …
Brain tumor detection using proper orthogonal decomposition integrated with deep learning networks
Abstract Background and Objective The central organ of the human nervous system is the
brain, which receives and sends stimuli to the various parts of the body to engage in daily …
brain, which receives and sends stimuli to the various parts of the body to engage in daily …
Multimodal ML Strategies for Wind Turbine Condition Monitoring in Heterogeneous IoT Data Environments
SS Jameel, SMKR Raazi, SM Jameel - … and Sustainability in the AIoT Era, 2024 - Springer
Addressing the pressing need for efficient wind turbine monitoring in the sustainable energy
sector, this paper begins with an extensive literature review focused on condition monitoring …
sector, this paper begins with an extensive literature review focused on condition monitoring …
Adaptive fine-tuning based transfer learning for the identification of MGMT promoter methylation status
E Schmitz, Y Guo, J Wang - Biomedical Physics & Engineering …, 2024 - iopscience.iop.org
Background. Glioblastoma Multiforme (GBM) is an aggressive form of malignant brain tumor
with a generally poor prognosis. O 6-methylguanine-DNA methyltransferase (MGMT) …
with a generally poor prognosis. O 6-methylguanine-DNA methyltransferase (MGMT) …
Unmasking unlearnable models: a classification challenge for biomedical images without visible cues
Predicting traits from images lacking visual cues is challenging, as algorithms are designed
to capture visually correlated ground truth. This problem is critical in biomedical sciences …
to capture visually correlated ground truth. This problem is critical in biomedical sciences …
3D MRI Brain Tumor Diagnosis with Topological Descriptors
H Daruger, DJ Brodsky, B Coskunuzer - International MICCAI Brainlesion …, 2023 - Springer
In this paper, we introduce a novel approach that utilizes topological data analysis (TDA) in
conjunction with MRI for determining glioma grade and identifying genomic biomarkers. The …
conjunction with MRI for determining glioma grade and identifying genomic biomarkers. The …
The power of integrating multiple data sources in medical imaging: A study of MGMT methylation status
M Miteva, M Nisheva-Pavlova - Procedia Computer Science, 2024 - Elsevier
The integration of multiple data sources is becoming increasingly important in the field of
medical imaging for the purpose of improving predictions. In this study, we investigated the …
medical imaging for the purpose of improving predictions. In this study, we investigated the …
[PDF][PDF] AI in healthcare: Activities of the University of Naples Federico II node of the CINI-AIIS Lab.
Artificial Intelligence (AI) embraces techniques and algorithms that, over the years, have
been applied to different fields and domains. The complexity and rise of data in healthcare …
been applied to different fields and domains. The complexity and rise of data in healthcare …