Latest AI and machine learning research in oncology/hematology for healthcare professionals.
BACKGROUND: Disulfidptosis is a novel form of glucose starvation-induced cell death, yet its prognostic implications in gastric cancer (GC) remain largely undefined. METHODS: We integrated single-cell and bulk multi-omics data to identify core disulfidptosis-related genes. A robust Cox regression-based prognostic model was constructed. Machine learning combined with single-cell interaction analyse...
Metals and metalloids play essential roles in cancer biology, influencing redox balance, epigenetic regulation, immune responses, and cell death throughout tumour development, progression, and resistance to therapy. Despite this broad biological relevance, the systematic clinical integration of metallomics into oncology remains in its early stages. This review introduces the Cancer Metallome Conti...
PURPOSE: The ENZAMET trial established that enzalutamide added to androgen deprivation therapy (ADT) improves overall survival (OS) in metastatic horm...
Prostate cancer (PCa) is one of the most prevalent malignancies in men worldwide, and metabolic reprogramming particularly of lipid metabolism plays a...
OBJECTIVE: Accurate attenuation correction (AC) is critical in quantitative brain PET imaging. Conventional CT-based AC methods increase radiation exp...
This work aims to develop a digital twin (DT) framework for fast online adaptive proton therapy planning in prostate stereotactic body radiation thera...
Bone and soft tissue tumors (BSTTs) are prone to metastasize to the lungs to form pulmonary nodules, which are quite different from other metastatic n...
Lung carcinoma is regarded as lung cancer and is the usual form of cancers worldwide. It cannot be diagnosed easily until it spreads and is regarded a...
Triple-negative breast cancer (TNBC) is an oncology indication with urgent need for drug discovery and limited targeted therapies. This work benchmark...
Triple-negative breast cancer (TNBC) patients often ential hypertension, yet how systemic vascular stress synergizes with tumor aggressiveness to driv...
The urgent need for innovative cancer therapies has driven increasing interest in repurposing drugs originally developed for non-oncological diseases....
PURPOSE: Non-small cell lung cancer (NSCLC) remains a major clinical challenge, with Programmed death-ligand 1 (PD-L1) expression serving as a crucial...
BACKGROUND: Mutations in CTNNB1 are recognized oncogenic drivers of hepatocellular carcinoma (HCC); however, the downstream effector molecules and the...
PURPOSE OF REVIEW: Artificial intelligence (AI) is increasingly integrated into robotic-assisted surgery, transforming digital surgical platforms into...
Due to its high genomic heterogeneity and dense desmoplastic microenvironment, traditional diagnosis and treatment for pancreatic ductal adenocarcinom...
The field of oncology has witnessed remarkable progress with the integration of high-tech innovations in tumor ablation. Tumor ablation therapies, suc...
OBJECTIVE: Glioblastoma (GBM) is the most aggressive type of intracranial malignant tumor, known for its extremely poor prognosis. Lactylation, a newl...
BACKGROUND: Diagnostics and therapeutics for corneal nerve pathologies are rapidly evolving, with continual advancements in imaging, laser, machine le...
We propose Open Immune Oncology (OpenIO), a framework integrating generative AI and omics to advance precision oncology. By leveraging biological scal...
Cervical intraepithelial neoplasia is the primary type of cervical precancerous lesion; however, manual clinical diagnosis is prone to bias and has li...