Oncology/Hematology

Other Cancers

Latest AI and machine learning research in other cancers for healthcare professionals.

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Prediction of hepatocellular carcinoma response to radiation segmentectomy using an MRI-based machine learning approach.

PURPOSE: To evaluate the value of pre-treatment MRI-based radiomics in patients with hepatocellular ...

A Recognition System for Diagnosing Salivary Gland Neoplasms Based on Vision Transformer.

Salivary gland neoplasms (SGNs) represent a group of human neoplasms characterized by a remarkable c...

Machine learning-based new classification for immune infiltration of gliomas.

BACKGROUND: Glioma is a highly heterogeneous and poorly immunogenic malignant tumor, with limited ef...

Patient-Specific Deep Learning Tracking Framework for Real-Time 2D Target Localization in Magnetic Resonance Imaging-Guided Radiation Therapy.

PURPOSE: We propose a tumor tracking framework for 2D cine magnetic resonance imaging (MRI) based on...

An optimized siamese neural network with deep linear graph attention model for gynaecological abdominal pelvic masses classification.

An adnexal mass, also known as a pelvic mass, is a growth that develops in or near the uterus, ovari...

Aggressiveness classification of clear cell renal cell carcinoma using registration-independent radiology-pathology correlation learning.

BACKGROUND: Renal cell carcinoma (RCC) is a common cancer that varies in clinical behavior. Clear ce...

Robust brain MRI image classification with SIBOW-SVM.

Primary Central Nervous System tumors in the brain are among the most aggressive diseases affecting ...

Predicting Breast Cancer Relapse from Histopathological Images with Ensemble Machine Learning Models.

Relapse and metastasis occur in 30-40% of breast cancer patients, even after targeted treatments lik...

Multiparametric MRI-Based Deep Learning Models for Preoperative Prediction of Tumor Deposits in Rectal Cancer and Prognostic Outcome.

RATIONALE AND OBJECTIVES: To investigate the predictive value of a deep learning model based on mult...

Development and validation of a machine-learning model for preoperative risk of gastric gastrointestinal stromal tumors.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) have malignant potential, and treatment varies a...

Artificial intelligence and omics in malignant gliomas.

Glioblastoma multiforme (GBM) is one of the most common and aggressive type of malignant glioma with...

Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven Seven-Gene Stemness Signature That Predicts Progression.

Prostate cancer (PCa) poses a significant global health challenge, particularly due to its progressi...

Machine learning identification of NK cell immune characteristics in hepatocellular carcinoma based on single-cell sequencing and bulk RNA sequencing.

BACKGROUND: Hepatocellular carcinoma (HCC) is a highly malignant tumor; however, its immune microenv...

Advancing Anticancer Drug Discovery: Leveraging Metabolomics and Machine Learning for Mode of Action Prediction by Pattern Recognition.

A bottleneck in the development of new anti-cancer drugs is the recognition of their mode of action ...

Combining metabolomics and machine learning to discover biomarkers for early-stage breast cancer diagnosis.

There is an urgent need for better biomarkers for the detection of early-stage breast cancer. Utiliz...

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