Latest AI and machine learning research in skin cancer for healthcare professionals.
Gene-by-gene differential expression analysis is a widely used supervised approach for interpreting single-cell RNA-sequencing (scRNA-seq) data. However, modern scRNA-seq datasets often contain large numbers of cells, leading to the identification of many differentially expressed genes with extremely small p-values but negligible effect sizes, thus making biological interpretation difficult. To ov...
Programmed death ligand-1 (PD-L1) expression is a key biomarker for identifying non-small cell lung cancer (NSCLC) patients eligible for immunotherapy, but its immunohistochemistry assessment is subject to high interobserver variability. This study aimed to develop and validate an automated system based on artificial intelligence (AI) to detect and classify PD-L1-positive cells in digital lung bio...
BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) are associated with poor 5-year survival and substantial treatment-related morbidity. Neoadj...
BACKGROUND: Ammonia, long regarded as a metabolic waste product, has recently been recognized as a pivotal oncometabolite in the tumor microenvironmen...
The gut microbiome functions as a key regulator of tumorigenesis and progression, thereby modulating tumor development and treatment outcomes (includi...
Vasoactive intestinal peptide (VIP) plays a multifaceted role in cancer biology, yet its prognostic and immunological implications in melanoma remain ...
Skin cancer (SC) is one of the most prevalent forms of cancer worldwide. Both melanoma and non-melanoma types pose major challenges for early detectio...
BACKGROUND AND OBJECTIVE: Neoadjuvant immune-checkpoint inhibitors (ICIs) in muscle-invasive bladder cancer (MIBC) were tested in patient's ineligible...
Artificial intelligence (AI) can transform cancer immunotherapy by enabling more accurate prediction of treatment responses, the discovery of specific...
Artificial Intelligence (AI) is reshaping oncology by addressing key limitations in traditional cancer care and enabling data-driven, personalized app...
Systemic therapy for hepatocellular carcinoma (HCC) has undergone rapid transformation over the past decade, significantly expanding treatment options...
BACKGROUND: Lung adenocarcinoma (LUAD), the predominant histological subtype of non-small cell lung cancer, remains a leading cause of cancer-related ...
Quantitative imaging is an emerging field that may allow prediction of oncological outcomes. We investigate whether radiomics and deep learning can pr...
Nanomedicine-based cancer immunotherapy integrates nanotechnology with immune modulation, representing a promising strategy to improve both the effica...
This review systematically analyzes the relationship between the immune microenvironment characteristics of microsatellite instability-high (MSI-H) or...
BACKGROUND: Glioblastoma (GBM) is the most common malignant glioma in adults. It has an extremely poor prognosis, highlighting an urgent need for new ...
BACKGROUND: R-loops regulate genome stability and transcription, but their roles in uveal melanoma (UVM) are unclear. METHODS: A total of 1,185 R-loop...
PURPOSE: To investigate the prognostic value of an artificial intelligence (AI)-based semi-automated tool for longitudinal whole-body quantification o...
The gut microbiota appears to play a critical role in modulating antitumor immune responses and influencing the efficacy of cancer immunotherapy drugs...
Cancer immunotherapy has revolutionised oncology by utilising immune-mediated mechanisms to achieve durable anti-tumour responses and long-term clinic...