Latest AI and machine learning research in other cancers for healthcare professionals.
BACKGROUND AND AIM: Currently available staging systems for cholangiocarcinoma (CCA) are not applica...
Accurate and automatic brain metastases target delineation is a key step for efficient and effective...
Cancer is caused by germline and somatic mutations, which can share biological features such as amin...
OBJECTIVES: Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal carcinom...
The aim of this study was to investigate the impact of pixel-based machine learning (ML) techniques,...
Colorectal cancer (CRC) a leading cause of death by cancer, and screening programs for its early ide...
In this research, we exploited the deep learning framework to differentiate the distinctive types of...
In this study, gene expression profiles of osteosarcoma (OS) were analyzed to identify critical gene...
Recently, microRNAs (miRNAs) are confirmed to be important molecules within many crucial biological ...
Depressive symptoms occur frequently in patients with schizophrenia. Several factor analytical studi...
Lung cancer is one of the most common malignancies and has a low 5-year survival rate. There are no ...
PURPOSE: Gliomas are rapidly progressive, neurologically devastating, largely fatal brain tumors. Ma...
Cross-sectional X-ray imaging has become the standard for staging most solid organ malignancies. How...
Functional thyroid carcinoma is an unusual cause of thyrotoxicosis. We describe the clinical present...
OBJECTIVES: Based on data from Chinese and Indian traditional herbal medicines, gum resin of (somet...
OBJECTIVE: Active surveillance (AS) offers a strategy to reduce overtreatment and now is a widely ac...
Automated breast cancer multi-classification from histopathological images plays a key role in compu...
PURPOSE: Disease staging involves the assessment of disease severity or progression and is used for ...
Hepatocellular carcinoma (HCC) is the main cause of mortality in patients with chronic viral hepatit...
Deep learning using convolutional neural networks is an actively emerging field in histological imag...
We aimed to identify optimal machine-learning methods for radiomics-based prediction of local failur...