Oncology/Hematology

Brain Cancer

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

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AS-NeSt: A Novel 3D Deep Learning Model for Radiation Therapy Dose Distribution Prediction in Esophageal Cancer Treatment With Multiple Prescriptions.

PURPOSE: Implementing artificial intelligence technologies allows for the accurate prediction of rad...

Hydrogel spacer injection to the meso-sigmoid to protect the sigmoid colon in cervical cancer brachytherapy: A technical report.

PURPOSE: The use of a hydrogel spacer inserted into recto-vaginal fossa is a valuable strategy to mi...

Detection and classification of brain tumor using hybrid deep learning models.

Accurately classifying brain tumor types is critical for timely diagnosis and potentially saving liv...

Pembrolizumab alters the tumor immune landscape in a patient with dMMR glioblastoma.

Congenital DNA mismatch repair defects (dMMR), such as Lynch Syndrome, predispose patients to a vari...

Synergizing photon-counting CT with deep learning: potential enhancements in medical imaging.

This review article highlights the potential of integrating photon-counting computed tomography (CT)...

Tailored Intraoperative MRI Strategies in High-Grade Glioma Surgery: A Machine Learning-Based Radiomics Model Highlights Selective Benefits.

BACKGROUND AND OBJECTIVES: In high-grade glioma (HGG) surgery, intraoperative MRI (iMRI) has traditi...

A Short Review on the Impact of Artificial Intelligence in Diagnosis Diseases: Role of Radiomics In Neuro-Oncology.

Artificial Intelligence (AI) is rapidly transforming various aspects of healthcare, including the fi...

StemnesScoRe: an R package to estimate the stemness of glioma cancer cells at single-cell resolution.

BACKGROUND/AIM: Glioblastoma is the most heterogeneous and the most difficult-to-treat type of brain...

Artificial intelligence in neuro-oncology.

Artificial intelligence (AI) describes the application of computer algorithms to the solution of pro...

Identification of IDH and TERTp mutations using dynamic susceptibility contrast MRI with deep learning in 162 gliomas.

PURPOSE: Isocitrate dehydrogenase (IDH) and telomerase reverse transcriptase gene promoter (TERTp) m...

An End-to-end and Drug Repurposing Pipeline for Glioblastoma.

Our study aims to address the challenges in drug development for glioblastoma, a highly aggressive b...

Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology.

INTRODUCTION: Combination immunotherapy holds promise for improving survival in responsive glioblast...

Single-Cell Radiation Response Scoring with the Deep Learning Algorithm CeCILE 2.0.

External stressors, such as ionizing radiation, have massive effects on life, survival, and the abil...

Deep Learning-Guided Dosimetry for Mitigating Local Failure of Patients With Non-Small Cell Lung Cancer Receiving Stereotactic Body Radiation Therapy.

PURPOSE: Non-small cell lung cancer (NSCLC) stereotactic body radiation therapy with 50 Gy/5 fractio...

Meningioma consistency assessment based on the fusion of deep learning features and radiomics features.

PURPOSE: This study aims to combine deep learning features with radiomics features for the computer-...

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