Latest AI and machine learning research in other cancers for healthcare professionals.
Liver fibrosis staging (LFS) informs treatment decisions and prognostic assessment in liver disease....
BACKGROUND: Accurate tumor node metastasis (TNM) staging is fundamental for treatment planning and p...
Ki-67 is a critical prognostic marker for hepatocellular carcinoma (HCC), yet its clinical assessmen...
Electrical bioimpedance (EBI) measurement provides insights into the biophysical properties of tissu...
AIMS: To develop, deploy and evaluate artificial intelligence (AI) for triaging duodenal biopsies wi...
Early postoperative recurrence is a major cause of treatment failure in patients with locally advanc...
Immunotherapy has seen success in treating patients with cancer, but variable responses underscore t...
BACKGROUND: Clinical images are essential in plastic and reconstructive surgery education, particula...
Large-core anterior circulation ischemic stroke (LCIS) complicated by malignant cerebral edema (MCE)...
BACKGROUND: The assessment of estrogen/progesterone receptors (ER/PR) and human epidermal growth fac...
BACKGROUND: Lack of readily available recurrence data has limited the use of electronic health recor...
RATIONALE AND OBJECTIVES: Preoperative differentiation between follicular thyroid carcinoma (FTC) an...
BACKGROUND: Osteosarcoma (OS) is an aggressive bone malignancy with a poor prognosis. Dysregulated c...
RATIONALE AND OBJECTIVES: Nasopharyngeal carcinoma (NPC) is characterized by a distinctive virologic...
Accurate histopathological classification of renal cell carcinoma (RCC), along with its distinction ...
BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common types of cancer globally. Howev...
BACKGROUND: Breast cancer metastasis remains a major clinical challenge due to its complex molecular...
Precise survival risk stratification for bladder urothelial carcinoma (BUC) remains a clinical chall...
Abnormal glycolysis is one of the hallmarks of cancer and plays a significant role in its progressio...
BACKGROUND: To identify novel periodontal phenotypes using unsupervised machine learning on a large-...
PURPOSE: To evaluate the value of integrating habitat radiomics features and deep learning features ...