Latest AI and machine learning research in oncology/hematology for healthcare professionals.
BACKGROUND: Ovarian cancer is a gynecological malignancy associated with high mortality and poses significant clinical challenges in early diagnosis and precision treatment. Although the rapid advancement of artificial intelligence (AI) has introduced novel approaches to this field, a comprehensive bibliometric overview remains lacking. This study aims to fill this gap by providing a systematic bi...
BACKGROUND: N7-methylguanosine (m7G) modification plays a critical role in RNA metabolism and is increasingly recognized for its implications in cancer biology. It can influence RNA stability, translation efficiency, and gene expression regulation. However, the specific role of m7G modification and its downstream genes in thyroid carcinoma (THCA) is not well understood. To comprehensively explore ...
Complex algorithms and prediction models are increasingly being developed, investigated and applied for clinical use in medical laboratories and beyon...
OBJECTIVE: We investigated neurotensin receptor 1 (NTSR1) as a potential mediator of the mechanical immune barrier that contributes to T-cell exclusio...
Brain tumors represent a major global health challenge, and accurate classification of brain tumors is essential for effective diagnosis and treatment...
BACKGROUND: Elderly patients with acute myeloid leukemia (AML) exhibit considerable biological and clinical heterogeneity, hindering precise prognosis...
INTRODUCTION: Non-small cell lung cancer (NSCLC) remains the leading cause of cancer-related mortality worldwide, largely due to late-stage diagnosis ...
NTRK fusion is a promising therapeutic target for salivary gland cancer (SGC). However, the diagnostic complexity of the histological SGC subtype and ...
Combination strategy is crucial for enhancing cancer therapeutic efficacy, but co-delivery of multiple active pharmaceutical ingredients (APIs) remain...
OBJECTIVE: To investigate MRI-based radiomic features in glioma and key genes related to IDH mutations, and to analyze their correlation. METHODS: 61 ...
BACKGROUND/AIMS: Accurate prediction of the lymph node status is essential for clinical decision-making in breast cancer. This work aimed to develop a...
BACKGROUND: Gene-wise intratumor heterogeneity (ITH), defined as spatial variability in the expression of individual genes across tumor regions, remai...
The appendix is involved in a diverse spectrum of inflammatory, infectious, benign, and malignant conditions that extend far beyond acute appendicitis...
CT radiomics-based machine learning has potential to predict lung cancer in pulmonary nodules (PNs) earlier than standard-of-care methods. Low maligna...
Engineered neutrophils, modified via advanced biotechnological tools, are emerging as pivotal agents in translational medicine. By integrating gene ed...
Glioblastoma (GBM) is characterized by profound intratumoral heterogeneity and an immunosuppressive microenvironment that drive therapeutic resistance...
Fluorescence-guided imaging has increasingly been integrated into robot-assisted urologic surgery to improve intraoperative visualization of vascular ...
PURPOSE: To develop and externally validate an MRI-based deep learning framework for automated 3D segmentation of neck lymph nodes (LNs) in head and n...
AIMS: Global longitudinal strain (GLS) is essential for the early detection of cancer therapy-related cardiac dysfunction (CTRCD). A fully automated e...
Posttranslational modification (PTM) is pivotal in cancer progression. However, the mechanisms, biological function, and clinical significance underly...