Latest AI and machine learning research in oncology/hematology for healthcare professionals.
BACKGROUND: Accurate detection of lymph node metastasis is crucial for precise tumour staging and treatment planning. Conventional pathological examination can overlook lymph node micrometastasis, resulting in underdiagnosis and suboptimal clinical outcomes. This study aimed to develop a pan-cancer artificial intelligence diagnostic model (PanCAM) for detecting lymph node metastasis across cancer ...
OBJECTIVE: Pheochromocytoma and paraganglioma (PPGL) have high genetic predisposition rates. In this multicenter study, we aimed to identify risk-modulating factors for disease development and aggressiveness in patients carrying pathogenic variants (PPGLgPV) related to PPGL genes. METHODS: Observational prospective study including patients with PPGL, family history of PPGL or suspected PPGL-relate...
OBJECTIVES: To evaluate the diagnostic value of a machine learning (ML) model based on multi-modal ultrasound features in differentiating benign from ...
PURPOSE: The aim of this study was to develop and compare two intelligent model for stratifying the severity of acute radiation syndrome (ARS) in huma...
Cancer prevalence in the world has been attributed to exposure to air pollutants. However, spatial analyses utilizing remote sensing data have been li...
Glioblastoma (GB), the most aggressive primary brain tumor, is characterized by profound inter- and intratumoral heterogeneity and a highly immunosupp...
Preoperatively distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA) remains a significant clinical challenge. Curre...
BACKGROUND: Artificial intelligence-based radiomic approaches have been shown to accurately evaluate indeterminate pulmonary nodules. With the expansi...
BACKGROUND: Lentigo maligna (LM) and lentigo maligna melanoma (LMM) are difficult to manage because of their subclinical extension and ill-defined mar...
Chimeric antigen receptor (CAR) T-cell therapy has transformed the management of hematologic malignancies, achieving high remission rates in relapsed ...
Therapeutic resistance remains the principal barrier to durable clinical benefit in oncology, particularly in oncogene-driven malignancies and immune-...
Time-of-flight (ToF) in PET improves image quality by enhancing the signal-to-noise ratio, and recent deep learning (DL)-based ToF (DL-ToF) methods fu...
BACKGROUND: Sinonasal inverted papilloma(SNIP) is a benign tumor with a potential of malignant transformation but has a certain recurrence. OBJECTIVES...
Early detection of lung cancer remains critical for improving patient survival, yet current imaging-based screening methods are costly, invasive, and ...
As artificial intelligence (AI) has been proposed to aid in the clinical management of leukemia, we sought to summarize the most relevant, current lit...
Cells must adopt flexible regulatory strategies to make decisions regarding their fate, including differentiation, apoptosis, or survival in the face ...
Digital breast tomosynthesis (DBT) increases sensitivity and specificity compared to digital mammography (DM) in the early detection of breast cancer....
BACKGROUND AND PURPOSE: The telomerase reverse transcriptase (TERT) gene promoter mutation is a crucial factor for identifying an isocitrate dehydroge...
Breast cancer diagnosis from histopathological images remains a critical yet challenging task due to staining variability, magnification differences, ...
Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both healthy and diseased tissues1,2. These fragments carry r...