Latest AI and machine learning research in oncology/hematology for healthcare professionals.
RATIONALE AND OBJECTIVES: Nasopharyngeal carcinoma (NPC) is characterized by a distinctive virologic...
The use of multimodal data is essential for the precise diagnosis and treatment of brain tumors. In ...
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...
Glycans are complex carbohydrates that are integral to cancer progression and tumor biology. Convent...
We present a large whole-body and total-body curated dataset of dual-modality 2-deoxy-2-[18F]fluoro-...
Artificial intelligence (AI) offers a powerful means to accelerate precision oncology by individuali...
Precise survival risk stratification for bladder urothelial carcinoma (BUC) remains a clinical chall...
The FUCCI sensor fluorescently labels cell cycle phases, which is essential to assess normal and abn...
BACKGROUND: Lung cancer remains a leading cause of cancer-related mortality worldwide, highlighting ...
The therapeutic gain ratio (TGR) of radiotherapy for hepatocellular carcinoma (HCC) remains limited ...
BACKGROUND CONTEXT: Distinguishing malignant metastatic lesions from benign osteoporotic vertebral c...
PURPOSE: To characterize clinicopathologic and imaging differences between ocular adnexal mucosa-ass...
OBJECTIVE: The increasing global demand to assess pediatric skeletal malocclusions poses a growing c...
OBJECTIVE: To understand whether cancer-neutral image attributes (breast area and number of slices) ...
Abnormal glycolysis is one of the hallmarks of cancer and plays a significant role in its progressio...
PURPOSE: In this prospective cross-over study, the precision of manual correction of the clinical ta...
BACKGROUND: Accurate prediction of early recurrence (ER) after radical resection remains a critical ...
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 ...