Latest AI and machine learning research in other cancers for healthcare professionals.
BACKGROUND: Machine learning (ML) may provide novel insights into data patterns and improve model pr...
Radiotherapy is recognized as the major treatment of nasopharyngeal carcinoma. Rapid and accurate do...
Artificial intelligence (AI) is reshaping allergy and immunology by integrating cutting-edge technol...
AIM: To develop a machine learning-based CT radiomics model to preoperatively diagnose occult perito...
INTRODUCTION: - Accurate detection, segmentation, and volumetric analysis of brain lesions are essen...
Bone metastasis (BM) is a serious clinical symptom of advanced colorectal cancer. However, there is...
PURPOSE: To build and validate a combined radiomics and machine learning (ML) approach using B-mode ...
BACKGROUND AND AIMS: EUS is sensitive in detecting pancreatic neuroendocrine neoplasm (pNEN). Howeve...
OBJECTIVE: Advancements in early detection of the disease, prognosis and the development of therapeu...
Lung cancer is one of the most prevalent and lethal cancers. To improve health outcomes while reduci...
Lung cancer continues to be the leading cause of cancer-related mortality worldwide. Early detection...
The purpose of this study was to evaluate the performance of convolutional neural network (CNN)-base...
The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to th...
The proliferation of omics data has advanced cancer biomarker discovery but often falls short in ext...
BACKGROUND: Hepatocellular carcinoma (HCC) poses a significant global health challenge due to its po...
The parotid glands are the largest of the major salivary glands. They can harbour both benign and ma...
PURPOSE: Head and Neck (H&N) cancer accounts for 3% of cancer cases in the United States. Precise tu...
This study explores the bidirectional relation of esophageal squamous cell carcinoma (ESCC) and oral...
BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent tumor with high mortality rates. Computed ...
MicroRNAs (miRNA) are endogenous non-coding RNAs, typically around 23 nucleotides in length. Many mi...
This review examines the recent developments in deep learning (DL) techniques applied to multimodal ...