Oncology/Hematology

Brain Cancer

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

6,990 articles
Stay Ahead - Weekly Brain Cancer research updates
Subscribe
Browse Specialties
Showing 316-336 of 6,990 articles
Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current.

BACKGROUND: The low tube-voltage technique (e.g., 80 kV) can efficiently reduce the radiation dose a...

Convolutional neural network-assisted Raman spectroscopy for high-precision diagnosis of glioblastoma.

Glioblastoma multiforme (GBM) is the most lethal intracranial tumor with a median survival of approx...

Proximity adjusted centroid mapping for accurate detection of nuclei in dense 3D cell systems.

In the past decade, deep learning algorithms have surpassed the performance of many conventional ima...

Machine learning for predicting post-operative outcomes in meningiomas: a systematic review and meta-analysis.

PURPOSE: Meningiomas are the most common primary brain tumour and account for over one-third of case...

A Fusion Model of MRI Deep Transfer Learning and Radiomics for Discriminating between Pilocytic Astrocytoma and Adamantinomatous Craniopharyngioma.

RATIONALE AND OBJECTIVES: This study aimed to develop and validate a fusion model combining MRI deep...

Utility of Chatbot Literature Search in Radiation Oncology.

Artificial intelligence and natural language processing tools have shown promise in oncology by assi...

Personalized predictions of Glioblastoma infiltration: Mathematical models, Physics-Informed Neural Networks and multimodal scans.

Predicting the infiltration of Glioblastoma (GBM) from medical MRI scans is crucial for understandin...

Stress testing deep learning models for prostate cancer detection on biopsies and surgical specimens.

The presence, location, and extent of prostate cancer is assessed by pathologists using H&E-stained ...

Classification of speech arrests and speech impairments during awake craniotomy: a multi-databases analysis.

PURPOSE: Awake craniotomy presents a unique opportunity to map and preserve critical brain functions...

Tunable and real-time automatic interventional x-ray collimation from semi-supervised deep feature extraction.

BACKGROUND: The use of endovascular procedures is becoming increasingly popular across multiple clin...

UDA-GS: A cross-center multimodal unsupervised domain adaptation framework for Glioma segmentation.

Gliomas are the most common and malignant form of primary brain tumors. Accurate segmentation and me...

Real-time 3D MR guided radiation therapy through orthogonal MR imaging and manifold learning.

BACKGROUND: In magnetic resonance image (MRI)-guided radiotherapy (MRgRT), 2D rapid imaging is commo...

Breast radiotherapy planning: A decision-making framework using deep learning.

BACKGROUND: Effective breast cancer treatment planning requires balancing tumor control while minimi...

The G Protein-Coupled Receptor-Related Gene Signatures for Diagnosis and Prognosis in Glioblastoma: A Deep Learning Model Using RNA-Seq Data.

BACKGROUND: Glioblastoma (GBM) is the most aggressive cancer in the central nervous system in glial ...

Impact of deep learning reconstruction on radiation dose reduction and cancer risk in CT examinations: a real-world clinical analysis.

PURPOSE: The purpose of this study is to estimate the extent to which the implementation of deep lea...

MRI classification and discrimination of spinal schwannoma and meningioma based on deep learning.

BACKGROUD: Schwannoma (SCH) and meningiomas (MEN) are the two most common primary spinal cord tumors...

Segmentation of Low-Grade Brain Tumors Using Mutual Attention Multimodal MRI.

Early detection and precise characterization of brain tumors play a crucial role in improving patien...

Browse Specialties