AI Medical Compendium Topic

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Brain Neoplasms

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Brain multi modality image inpainting via deep learning based edge region generative adversarial network.

Technology and health care : official journal of the European Society for Engineering and Medicine
A brain tumor (BT) is considered one of the most crucial and deadly diseases in the world, as it affects the central nervous system and its main functions. Headaches, nausea, and balance problems are caused by tumors pressing on nearby brain tissue a...

Advancing brain tumor detection and classification in Low-Dose CT images using the innovative multi-layered deep neural network model.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundEffective brain tumour therapy and better patient outcomes depend on early tumour diagnosis. Accurate diagnosis can be hampered by traditional imaging techniques' frequent struggles with low resolution and noise, especially in Low Dose CT s...

Semisupervised adaptive learning models for IDH1 mutation status prediction.

PloS one
The mutation status of isocitrate dehydrogenase1 (IDH1) in glioma is critical information for the diagnosis, treatment, and prognosis. Accurately determining such information from MRI data has emerged as a significant research challenge in recent yea...

Brain tumor detection empowered with ensemble deep learning approaches from MRI scan images.

Scientific reports
Brain tumor detection is essential for early diagnosis and successful treatment, both of which can significantly enhance patient outcomes. To evaluate brain MRI scans and categorize them into four types-pituitary, meningioma, glioma, and normal-this ...

From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas.

Neurosurgical review
Gliomas are the most common primary tumors of the central nervous system, and advances in genetics and molecular medicine have significantly transformed their classification and treatment. This study aims to predict the IDH1 genotype in gliomas using...

Automatic smart brain tumor classification and prediction system using deep learning.

Scientific reports
A brain tumor is a serious medical condition characterized by the abnormal growth of cells within the brain. It can cause a range of symptoms, including headaches, seizures, cognitive impairment, and changes in behavior. Brain tumors pose a significa...

Leveraging TME features and multi-omics data with an advanced deep learning framework for improved Cancer survival prediction.

Scientific reports
Glioma, a malignant intracranial tumor with high invasiveness and heterogeneity, significantly impacts patient survival. This study integrates multi-omics data to improve prognostic prediction and identify therapeutic targets. Using single-cell data ...

Explainable deep stacking ensemble model for accurate and transparent brain tumor diagnosis.

Computers in biology and medicine
Early detection of brain tumors in MRI images is vital for improving treatment results. However, deep learning models face challenges like limited dataset diversity, class imbalance, and insufficient interpretability. Most studies rely on small, sing...

Identification of Recurrence-associated Gene Signatures and Machine Learning-based Prediction in IDH-Wildtype Histological Glioblastoma.

Journal of molecular neuroscience : MN
Glioblastoma (GBM) is a highly aggressive brain tumor with frequent recurrence, yet the molecular mechanisms driving recurrence remain poorly understood. Identifying recurrence-associated genes may improve prognosis and treatment strategies. We appli...

Machine learning in prediction of epidermal growth factor receptor status in non-small cell lung cancer brain metastases: a systematic review and meta-analysis.

BMC cancer
BACKGROUND: Epidermal growth factor receptor (EGFR) mutations are present in 10-60% of all non-small cell lung cancer (NSCLC) patients and are associated with dismal prognosis. Lung cancer brain metastases (LCBM) are a common complication of lung can...