Oncology/Hematology

Brain Cancer

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

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SG-Fusion: A swin-transformer and graph convolution-based multi-modal deep neural network for glioma prognosis.

The integration of morphological attributes extracted from histopathological images and genomic data...

Artificial intelligence for response prediction and personalisation in radiation oncology.

Artificial intelligence (AI) systems may personalise radiotherapy by assessing complex and multiface...

Cross-view discrepancy-dependency network for volumetric medical image segmentation.

The limited data poses a crucial challenge for deep learning-based volumetric medical image segmenta...

The Role of Artificial Intelligence on Tumor Boards: Perspectives from Surgeons, Medical Oncologists and Radiation Oncologists.

The integration of multidisciplinary tumor boards (MTBs) is fundamental in delivering state-of-the-a...

Accurate low and high grade glioma classification using free water eliminated diffusion tensor metrics and ensemble machine learning.

Glioma, a predominant type of brain tumor, can be fatal. This necessitates an early diagnosis and ef...

Automated brain tumor diagnostics: Empowering neuro-oncology with deep learning-based MRI image analysis.

Brain tumors, characterized by the uncontrolled growth of abnormal cells, pose a significant threat ...

Metabolic signatures derived from whole-brain MR-spectroscopy identify early tumor progression in high-grade gliomas using machine learning.

PURPOSE: Recurrence for high-grade gliomas is inevitable despite maximal safe resection and adjuvant...

Sexually dimorphic computational histopathological signatures prognostic of overall survival in high-grade gliomas via deep learning.

High-grade glioma (HGG) is an aggressive brain tumor. Sex is an important factor that differentially...

Multiparametric Ultrasound Imaging of Prostate Cancer Using Deep Neural Networks.

OBJECTIVE: A deep neural network (DNN) was trained to generate a multiparametric ultrasound (mpUS) v...

Deep learning-based multimodal spatial transcriptomics analysis for cancer.

The advent of deep learning (DL) and multimodal spatial transcriptomics (ST) has revolutionized canc...

Real-time estimation of the optimal coil placement in transcranial magnetic stimulation using multi-task deep learning.

Transcranial magnetic stimulation (TMS) has emerged as a promising neuromodulation technique with bo...

Ensemble learning-based pretreatment MRI radiomic model for distinguishing intracranial extraventricular ependymoma from glioblastoma multiforme.

This study aims to develop an ensemble learning (EL) method based on magnetic resonance (MR) radiomi...

Utilizing machine learning to tailor radiotherapy and chemoradiotherapy for low-grade glioma patients.

BACKGROUND: There is ongoing uncertainty about the effectiveness of various adjuvant treatments for ...

Deep reinforcement learning in radiation therapy planning optimization: A comprehensive review.

PURPOSE: The formulation and optimization of radiation therapy plans are complex and time-consuming ...

Harnessing Deep Learning for Accurate Pathological Assessment of Brain Tumor Cell Types.

Primary diffuse central nervous system large B-cell lymphoma (CNS-pDLBCL) and high-grade glioma (HGG...

Development of deep learning-based novel auto-segmentation for the prostatic urethra on planning CT images for prostate cancer radiotherapy.

Urinary toxicities are one of the serious complications of radiotherapy for prostate cancer, and dos...

Automatic localization of anatomical landmarks in head cine fluoroscopy images via deep learning.

BACKGROUND: Fluoroscopy guided interventions (FGIs) pose a risk of prolonged radiation exposure; per...

A machine learning-based pipeline for multi-organ/tissue patient-specific radiation dosimetry in CT.

OBJECTIVES: To develop a machine learning-based pipeline for multi-organ/tissue personalized radiati...

Artificial Intelligence for Radiation Treatment Planning: Bridging Gaps From Retrospective Promise to Clinical Reality.

Artificial intelligence (AI) radiation therapy (RT) planning holds promise for enhancing the consist...

Three-Dimensional Deep Learning Normal Tissue Complication Probability Model to Predict Late Xerostomia in Patients With Head and Neck Cancer.

PURPOSE: Conventional normal tissue complication probability (NTCP) models for patients with head an...

Deep learning applied to dose prediction in external radiation therapy: A narrative review.

Over the last decades, the use of artificial intelligence, machine learning and deep learning in med...

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