Oncology/Hematology

Brain Cancer

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

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Showing 43-63 of 6,990 articles
Image quality and radiation dose of reduced-dose abdominopelvic computed tomography (CT) with silver filter and deep learning reconstruction.

To assess the image quality and radiation dose between reduced-dose CT with deep learning reconstruc...

Predicting the molecular subtypes of 2021 WHO grade 4 glioma by a multiparametric MRI-based machine learning model.

BACKGROUND: Accurately distinguishing the different molecular subtypes of 2021 World Health Organiza...

A comprehensive analysis of transcription factors identified TCF3 as a prognostic target for glioma.

Transcription factors (TFs) are pivotal in tumor initiation and progression, regulating downstream g...

Integrated clinicopathological-radiomic-blood model for glioma survival prediction via machine learning: a multicenter cohort study.

BACKGROUND: Glioma is characterized by a poor prognosis and limited possibilities for treatment. Pre...

Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.

Breast cancer continues to be a leading cause of death among women in the world. The prediction of s...

Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics.

Glioma is a highly heterogeneous and aggressive brain tumour that demands an integrated understandin...

AI Revolution in Radiology, Radiation Oncology and Nuclear Medicine: Transforming and Innovating the Radiological Sciences.

The integration of artificial intelligence (AI) into clinical practice, particularly within radiolog...

OMT and tensor SVD-based deep learning model for segmentation and predicting genetic markers of glioma: A multicenter study.

Glioma is the most common primary malignant brain tumor and preoperative genetic profiling is essent...

Post-hoc eXplainable AI methods for analyzing medical images of gliomas (- A review for clinical applications).

Deep learning (DL) has shown promise in glioma imaging tasks using magnetic resonance imaging (MRI) ...

Artificial intelligence-driven discovery of YH395A: A novel TGFβR1 inhibitor with potent anti-tumor activity against triple-negative breast cancer.

Characterized by high malignancy and limited treatment efficacy, triple-negative breast cancer (TNBC...

Dynamic abdominal MRI image generation using cGANs: A generalized model for various breathing patterns with extensive evaluation.

Organ motion is a limiting factor during the treatment of abdominal tumors. During abdominal interve...

AG-MS3D-CNN multiscale attention guided 3D convolutional neural network for robust brain tumor segmentation across MRI protocols.

Accurate segmentation of brain tumors from multimodal Magnetic Resonance Imaging (MRI) plays a criti...

Machine learning-assisted high-throughput prediction and experimental validation of high-responsivity extreme ultraviolet detectors.

Identifying materials with optimal optoelectronic properties for targeted applications represents bo...

pyDOSEIA: A Python Package for Radiological Impact Assessment during Long-term or Accidental Atmospheric Releases.

pyDOSEIA is a Python package designed for meteorological data processing and radiological impact ass...

Robot-Assisted Retrograde Intrarenal Surgery: A Mini Review of the Literature on Robotic Surgery Platforms for Endoscopic Stone Surgery.

Retrograde intrarenal surgery (RIRS) has become a cornerstone in renal stone management, with roboti...

Intelligent brain tumor detection using hybrid finetuned deep transfer features and ensemble machine learning algorithms.

Brain tumours (BTs) are severe neurological disorders. They affect more than 308,000 people each yea...

Leveraging pathological markers of lower grade glioma to predict the occurrence of secondary epilepsy, a retrospective study.

Epilepsy is a common manifestation in patients with lower grade glioma (LGG), often presenting as th...

Impact of Normal Lung Volume Choices on Radiation Pneumonitis Risk Prediction in Locally Non-small Cell Lung Cancer Radiation Therapy.

PURPOSE: This study aims to evaluate the impact of varying definitions of normal lung volume on the ...

A deep active learning framework for mitotic figure detection with minimal manual annotation and labelling.

AIMS: Accurately and efficiently identifying mitotic figures (MFs) is crucial for diagnosing and gra...

Integrating MobileNetV3 and SqueezeNet for Multi-class Brain Tumor Classification.

Brain tumors pose a critical health threat requiring timely and accurate classification for effectiv...

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