Oncology/Hematology

Brain Cancer

Latest AI and machine learning research in brain cancer for healthcare professionals.

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Showing 253-273 of 6,990 articles
Radiomics in glioma: emerging trends and challenges.

Radiomics is a promising neuroimaging technique for extracting and analyzing quantitative glioma fea...

A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things.

With bio-medical wearables becoming an essential part of Internet of Medical things (IoMT) for monit...

Predicting survival in malignant glioma using artificial intelligence.

Malignant gliomas, including glioblastoma, are amongst the most aggressive primary brain tumours, ch...

Machine learning models for water safety enhancement.

Humans encounter both natural and artificial radiation sources, including cosmic rays, primordial ra...

Detecting IDH and TERTp mutations in diffuse gliomas using H-MRS with attention deep-shallow networks.

BACKGROUND: Preoperative and noninvasive detection of isocitrate dehydrogenase (IDH) and telomerase ...

Radiogenomics and machine learning predict oncogenic signaling pathways in glioblastoma.

BACKGROUND: Glioblastoma (GBM) is a highly aggressive brain tumor associated with a poor patient pro...

Semiautomated Extraction of Research Topics and Trends From National Cancer Institute Funding in Radiological Sciences From 2000 to 2020.

PURPOSE: Investigators and funding organizations desire knowledge on topics and trends in publicly f...

Unrolled deep learning for breast cancer detection using limited-view photoacoustic tomography data.

Photoacoustic tomography (PAT) has emerged as a promising imaging modality for breast cancer detecti...

Can we rely on machine learning algorithms as a trustworthy predictor for recurrence in high-grade glioma? A systematic review and meta-analysis.

Early prediction of recurrence in high-grade glioma (HGG) is critical due to its aggressive nature a...

Deep learning classification of MGMT status of glioblastomas using multiparametric MRI with a novel domain knowledge augmented mask fusion approach.

We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparame...

Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment.

Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection ...

Breast radiation therapy fluence painting with multi-agent deep reinforcement learning.

BACKGROUND: The electronic compensation (ECOMP) technique for breast radiation therapy provides exce...

An interpretable multi-scale convolutional attention residual neural network for glioma grading with Raman spectroscopy.

Since the malignancy of gliomas varies with their grade, classifying gliomas of different grades can...

Modernizing Neuro-Oncology: The Impact of Imaging, Liquid Biopsies, and AI on Diagnosis and Treatment.

Advances in neuro-oncology have transformed the diagnosis and management of brain tumors, which are ...

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