Oncology/Hematology

Brain Cancer

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

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MRI-Based Meningioma Firmness Classification Using an Adversarial Feature Learning Approach.

The firmness of meningiomas is a critical factor that impacts the surgical approach recommended for ...

Predictive modeling with linear machine learning can estimate glioblastoma survival in months based solely on MGMT-methylation status, age and sex.

PURPOSE: Machine Learning (ML) has become an essential tool for analyzing biomedical data, facilitat...

[MP-MRI in the evaluation of non-operative treatment response, for residual and recurrent tumor detection in head and neck cancer].

As non-surgical therapies gain acceptance in head and neck tumors, the importance of imaging has inc...

AI for image quality and patient safety in CT and MRI.

Substantial endeavors have been recently dedicated to developing artificial intelligence (AI) soluti...

Explainable AI-driven prediction of APE1 inhibitors: enhancing cancer therapy with machine learning models and feature importance analysis.

The viability of cells and the integrity of the genome depend on the detection and repair of damaged...

Explainable artificial intelligence of DNA methylation-based brain tumor diagnostics.

We have recently developed a machine learning classifier that enables fast, accurate, and affordable...

Soft-tissue metastasis in esophageal cancer managed by dose escalation radiation therapy: a clinical case and review of literature.

Soft tissue metastasis in esophageal cancer is a very rare entity. A 76-year-old man was referred fo...

Comparative analysis for accurate multi-classification of brain tumor based on significant deep learning models.

Brain tumours are a significant health concern, often resulting in severe cognitive and physiologica...

Integration of 101 machine learning algorithm combinations to unveil m6A/m1A/m5C/m7G-associated prognostic signature in colorectal cancer.

Colorectal cancer (CRC) is the most common malignancy in the digestive system, with a lower 5-year o...

Long-term solar radiation forecasting in India using EMD, EEMD, and advanced machine learning algorithms.

Solar radiation plays a critical role in the carbon sequestration processes of terrestrial ecosystem...

Radiation oncology at crossroads: Rise of AI and managing the unexpected.

Integrating artificial intelligence (AI) into radiation oncology has revolutionized clinical workflo...

Machine learning-based integration develops a hypoxia-derived signature for improving outcomes in glioma.

The growth of glioma is frequently accompanied by a hypoxic microenvironment. Nevertheless, the clin...

MLAR-UNet: LDCT image denoising based on U-Net with multiple lightweight attention-based modules and residual reinforcement.

Computed tomography (CT) is a crucial medical imaging technique which uses x-ray radiation to identi...

Does Deep Learning Reconstruction Improve Ureteral Stone Detection and Subjective Image Quality in the CT Images of Patients with Metal Hardware?

Diagnosing ureteral stones with low-dose CT in patients with metal hardware can be challenging beca...

A promising AI based super resolution image reconstruction technique for early diagnosis of skin cancer.

Skin cancer can be prevalent in people of any age group who are exposed to ultraviolet (UV) radiatio...

A privacy-preserved horizontal federated learning for malignant glioma tumour detection using distributed data-silos.

Malignant glioma is the uncontrollable growth of cells in the spinal cord and brain that look simila...

Assessing multiple MRI sequences in deep learning-based synthetic CT generation for MR-only radiation therapy of head and neck cancers.

PURPOSE: This study investigated the effect of multiple magnetic resonance (MR) sequences on the qua...

A deep ensemble learning framework for glioma segmentation and grading prediction.

The segmentation and risk grade prediction of gliomas based on preoperative multimodal magnetic reso...

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