Oncology/Hematology

Brain Cancer

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

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Clinical impact of an explainable machine learning with amino acid PET imaging: application to the diagnosis of aggressive glioma.

PURPOSE: Radiomics-based machine learning (ML) models of amino acid positron emission tomography (PE...

Evaluation of a Deep Learning Denoising Algorithm for Dose Reduction in Whole-Body Photon-Counting CT Imaging: A Cadaveric Study.

RATIONALE AND OBJECTIVES: Photon Counting CT (PCCT) offers advanced imaging capabilities with potent...

Current state and promise of user-centered design to harness explainable AI in clinical decision-support systems for patients with CNS tumors.

In neuro-oncology, MR imaging is crucial for obtaining detailed brain images to identify neoplasms, ...

Integration of histone modification-based risk signature with drug sensitivity analysis reveals novel therapeutic strategies for lower-grade glioma.

BACKGROUND: Lower-grade glioma (LGG) exhibits significant heterogeneity in clinical outcomes, and cu...

A hybrid explainable model based on advanced machine learning and deep learning models for classifying brain tumors using MRI images.

Brain tumors present a significant global health challenge, and their early detection and accurate c...

Diagnostic Accuracy of Ambient Mass Spectrometry with Blood Plasma in a Murine Glioma Model Using Machine Learning.

OBJECTIVE: Malignant glioma progresses rapidly and shows poor prognosis, but clinically applicable b...

Brain tumour histopathology through the lens of deep learning: A systematic review.

PROBLEM: Machine learning (ML)/Deep learning (DL) techniques have been evolving to solve more comple...

Artificial Intelligence, Machine Learning and Big Data in Radiation Oncology.

This review explores the applications of artificial intelligence and machine learning (AI/ML) in rad...

Impact of glioma metabolism-related gene ALPK1 on tumor immune heterogeneity and the regulation of the TGF-β pathway.

BACKGROUND: Recent years have seen persistently poor prognoses for glioma patients. Therefore, explo...

Feasibility of reconstructingpatient 3D dose distributions from 2D EPID image data using convolutional neural networks.

. The primary purpose of this work is to demonstrate the feasibility of a deep convolutional neural ...

Dual-path neural network extracts tumor microenvironment information from whole slide images to predict molecular typing and prognosis of Glioma.

BACKGROUND AND OBJECTIVE: Utilizing AI to mine tumor microenvironment information in whole slide ima...

Weakly supervised deep learning-based classification for histopathology of gliomas: a single center experience.

Multiple artificial intelligence systems have been created to facilitate accurate and prompt histopa...

Multiparametric MRI along with machine learning predicts prognosis and treatment response in pediatric low-grade glioma.

Pediatric low-grade gliomas (pLGGs) exhibit heterogeneous prognoses and variable responses to treatm...

A GPU-accelerated fuzzy method for real-time CT volume filtering.

During acquisition and reconstruction, medical images may become noisy and lose diagnostic quality. ...

Cooperative multi-task learning and interpretable image biomarkers for glioma grading and molecular subtyping.

Deep learning methods have been widely used for various glioma predictions. However, they are usuall...

Performance of Convolutional Neural Network Models in Meningioma Segmentation in Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis.

BACKGROUND: Meningioma, the most common primary brain tumor, presents significant challenges in MRI-...

A machine learning-assisted systematic review of preclinical glioma modeling: Is practice changing with the times?

BACKGROUND: Despite improvements in our understanding of glioblastoma pathophysiology, there have be...

Differentiation of glioblastoma G4 and two types of meningiomas using FTIR spectra and machine learning.

Brain tumors are among the most dangerous, due to their location in the organ that governs all life ...

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