An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review

S Das, GK Nayak, L Saba, M Kalra, JS Suri… - Computers in biology and …, 2022 - Elsevier
Background Artificial intelligence (AI) has become a prominent technique for medical
diagnosis and represents an essential role in detecting brain tumors. Although AI-based …

Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data

G Lorenzo, SR Ahmed, DA Hormuth II… - Annual Review of …, 2024 - annualreviews.org
Despite the remarkable advances in cancer diagnosis, treatment, and management over the
past decade, malignant tumors remain a major public health problem. Further progress in …

Integrating imaging and genomic data for the discovery of distinct glioblastoma subtypes: a joint learning approach

J Guo, A Fathi Kazerooni, E Toorens, H Akbari, F Yu… - Scientific Reports, 2024 - nature.com
Glioblastoma is a highly heterogeneous disease, with variations observed at both
phenotypical and molecular levels. Personalized therapies would be facilitated by non …

A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data

B Ocaña-Tienda, J Pérez-Beteta, JD Villanueva-García… - Scientific data, 2023 - nature.com
Brain metastasis (BM) is one of the main complications of many cancers, and the most
frequent malignancy of the central nervous system. Imaging studies of BMs are routinely …

Machine learning empowered brain tumor segmentation and grading model for lifetime prediction

M Renugadevi, K Narasimhan, CV Ravikumar… - IEEE …, 2023 - ieeexplore.ieee.org
An uncontrolled growth of brain cells is known as a brain tumor. When brain tumors are
accurately and promptly diagnosed using magnetic resonance imaging scans, it is easier to …

Exploiting the gut microbiome for brain tumour treatment

L Keane, JF Cryan, JP Gleeson - Trends in Molecular Medicine, 2024 - cell.com
Increasing evidence suggests that the gut microbiome plays a key role in a host of
pathological conditions, including cancer. Indeed, the bidirectional communication that …

Time-to-event overall survival prediction in glioblastoma multiforme patients using magnetic resonance imaging radiomics

G Hajianfar, A Haddadi Avval, SA Hosseini… - La radiologia …, 2023 - Springer
Abstract Purpose Glioblastoma Multiforme (GBM) represents the predominant aggressive
primary tumor of the brain with short overall survival (OS) time. We aim to assess the …

[HTML][HTML] Dynamic architecture based deep learning approach for glioblastoma brain tumor survival prediction

DS Wankhede, R Selvarani - Neuroscience Informatics, 2022 - Elsevier
A correct diagnosis of brain tumours is crucial to making an accurate treatment plan for
patients with the disease and allowing them to live a long and healthy life. Among a few …

Brain tumor segmentation and overall survival period prediction in glioblastoma multiforme using radiomic features

S Das, S Bose, GK Nayak… - Concurrency and …, 2022 - Wiley Online Library
Glioblastoma multiforme (GBM or glioblastoma) is a fast‐growing glioma that are the most
invasive type of glial tumors, rapidly growing and commonly spreading into nearby brain …

Interpretable machine learning model to predict survival days of malignant brain tumor patients

S Rajput, RA Kapdi, MS Raval… - … Learning: Science and …, 2023 - iopscience.iop.org
An artificial intelligence (AI) model's performance is strongly influenced by the input features.
Therefore, it is vital to find the optimal feature set. It is more crucial for the survival prediction …