Emerging role of artificial intelligence in diagnosis, classification and clinical management of glioma

J Luo, M Pan, K Mo, Y Mao, D Zou - Seminars in Cancer Biology, 2023 - Elsevier
Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

Artificial intelligence-driven biomedical genomics

K Guo, M Wu, Z Soo, Y Yang, Y Zhang, Q Zhang… - Knowledge-Based …, 2023 - Elsevier
As genomic research becomes more complex and data-rich, artificial intelligence (AI) has
emerged as a crucial tool for processing and analyzing high-dimensional genomic data …

Deep learning radiomics of ultrasonography for comprehensively predicting tumor and axillary lymph node status after neoadjuvant chemotherapy in breast cancer …

J Gu, T Tong, D Xu, F Cheng, C Fang, C He, J Wang… - Cancer, 2023 - Wiley Online Library
Background Neoadjuvant chemotherapy (NAC) can downstage tumors and axillary lymph
nodes in breast cancer (BC) patients. However, tumors and axillary response to NAC are not …

Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: a neuro-oncological investigation

S Saxena, B Jena, B Mohapatra, N Gupta… - Computers in Biology …, 2023 - Elsevier
Abstract Background The O6-methylguanine-DNA methyltransferase (MGMT) is a
deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential …

[HTML][HTML] Vision transformer-based weakly supervised histopathological image analysis of primary brain tumors

Z Li, Y Cong, X Chen, J Qi, J Sun, T Yan, H Yang, J Liu… - IScience, 2023 - cell.com
Diagnosis of primary brain tumors relies heavily on histopathology. Although various
computational pathology methods have been developed for automated diagnosis of primary …

A novel MRI-based deep learning networks combined with attention mechanism for predicting CDKN2A/B homozygous deletion status in IDH-mutant astrocytoma

L Zhang, R Wang, J Gao, Y Tang, X Xu, Y Kan… - European …, 2024 - Springer
Objectives To develop a high-accuracy MRI-based deep learning method for predicting
cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) homozygous deletion status in …

Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysis

L Li, F Xiao, 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 …

[HTML][HTML] MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models

N Saeed, M Ridzuan, H Alasmawi, I Sobirov… - Medical Image …, 2023 - Elsevier
The number of studies on deep learning for medical diagnosis is expanding, and these
systems are often claimed to outperform clinicians. However, only a few systems have …

Association of partial T2-FLAIR mismatch sign and isocitrate dehydrogenase mutation in WHO grade 4 gliomas: results from the ReSPOND consortium

MD Lee, SH Patel, S Mohan, H Akbari, S Bakas… - Neuroradiology, 2023 - Springer
Abstract Purpose While the T2-FLAIR mismatch sign is highly specific for isocitrate
dehydrogenase (IDH)-mutant, 1p/19q-noncodeleted astrocytomas among lower-grade …

Artificial intelligence in the radiomic analysis of glioblastomas: A review, taxonomy, and perspective

M Zhu, S Li, Y Kuang, VB Hill, AB Heimberger… - Frontiers in …, 2022 - frontiersin.org
Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron
emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches …