Latest AI and machine learning research in skin cancer for healthcare professionals.
OBJECTIVE: The assessment of immunotherapy plays a pivotal role in the clinical management of skin melanoma. Graph neural networks (GNNs), alongside other deep learning algorithms and bioinformatics approaches, have demonstrated substantial promise in advancing cancer diagnosis and treatment strategies.
The combined analysis of dual diseases can provide new insights into pathogenic mechanisms, identify novel biomarkers, and develop targeted therapeutic strategies. Polycythemia vera (PV) is a chronic myeloproliferative neoplasm associated with a risk of acute myeloid leukemia (AML) transformation. However, the chronic nature of disease transformation complicates longitudinal high-throughput sequen...
BACKGROUND: Melanoma (SKCM) is an extremely aggressive form of cancer, characterized by high mortality rates, frequent metastasis, and limited treatme...
BACKGROUND: Neutrophils play a key role in the tumor microenvironment (TME); however, their functions in glioblastoma (GBM) are overlooked and insuffi...
Joint analysis of transcriptomic and T cell receptor (TCR) features at single-cell resolution provides a powerful approach for in-depth T cell immune ...
Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in the digestive tract, characterized by a high recurrence ra...
PURPOSE: The use of real-world data (RWD) in oncology is becoming increasingly important for clinical decision making and tailoring treatment. Despite...
AIM: To develop a positron emission tomography/computed tomography (PET/CT)-based radiomics model for predicting programmed cell death ligand 1 (PD-L1...
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict clas...
The growing application of immune checkpoint inhibitors (ICIs) in cancer immunotherapy has underscored the critical need for reliable methods to ident...
BACKGROUND: Ovarian cancer (OC), owing to its substantial heterogeneity and high invasiveness, has historically been devoid of precise, individualized...
Gastric cancer (GC) is a prevalent malignancy with a high mortality rate and limited treatment options. Aging significantly contributes to tumor progr...
Intratumor heterogeneity (ITH) is involved in tumor evolution and drug resistance. Drug sensitivity shows discrepancy in different breast cancer (BRCA...
With the rising demand for liver transplantation (LT), research on acute rejection (AR) has become increasingly diverse, yet no consensus has been rea...
BACKGROUND: Although immune checkpoint inhibitor (ICI) represents a significant breakthrough in cancer immunotherapy, only a few patients benefit from...
BACKGROUND: Prognostic histopathological features such as mitosis in melanoma are excluded from the staging systems due to inter-observer variability ...
Spatial omics technologies enable analysis of gene expression and interaction dynamics in relation to tissue structure and function. However, existing...
Immunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-small cell lung cancer (NSCLC). Currently, a limit...
A standard for reporting genetic pathology results currently does not exist as a consensus. While effective reports are produced, there is lack of con...
BACKGROUND: Evidence that artificial intelligence (AI) may improve melanoma detection has led to calls for increased human-AI collaboration in clinica...