Latest AI and machine learning research in other cancers for healthcare professionals.
BACKGROUND: Accurate preoperative assessment of lymph node metastasis (LNM) is crucial for treatment planning and prognostic stratification in patients with lung cancer. This study aimed to develop and validate a predictive model for LNM using radiomic features derived from non-contrast computed tomography (CT) combined with clinical characteristics. METHODS: A total of 403 patients with pathologi...
UNLABELLED: Perineural invasion (PNI) is an important pathologic feature of cervical cancer that is associated with poor prognosis and provides key information for clinical decisions. A better understanding of the molecular mechanisms underlying PNI could lead to improved patient treatment strategies. Here, we generated whole-exome, whole-genome, and RNA sequencing data from tumors and matched nor...
Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, primarily due to its low immunogenicity and immunosuppre...
OBJECTIVES: To develop and validate a machine learning model integrating ultrasound radiomics and clinicopathological parameters to predict intrahepat...
The early and precise diagnosis of gynecological malignancies, such as cervical cancer, is critical for improving patient treatments. Extracellular ve...
Zero echo time magnetic resonance imaging is an ultrashort echo time technique that enables computed tomography-like visualization of cortical and tra...
OBJECTIVES: To develop a Generative Adversarial Network (GAN) for generating virtual T2 fat-suppressed (T2FS) sequences from standard T1- and T2-weigh...
BACKGROUND: Pediatric cancer stage at diagnosis is critical for prognosis and research comparisons. The Toronto Pediatric Cancer Stage Guidelines stan...
Mechanical characterization of cancer tissues is crucial for understanding tumor progression and response to therapy. However, common mechanophenotypi...
The binding of peptides to class I major histocompatibility complex (MHCI) molecules is central to adaptive immunity, making the identification of imm...
Recent advances in artificial intelligence (AI) have enabled the rapid and accurate prediction of diverse protein structures. The predicted conformati...
Though critical, traditional diagnostic approaches such as X-ray, CT scans, bronchoscopy and tissue biopsy don't reliably detect lung cancer at early ...
Homologous recombination deficiency (HRD) plays a central role in the pathogenesis and therapeutic vulnerability of epithelial ovarian cancer (EOC), p...
MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression, and dysregulated miRNA expression has been implicated in multiple cancer h...
Artificial nanomaterials known as nanozymes, which possess inherent enzyme-mimetic characteristics, have transformed environmental research, biomedici...
INTRODUCTION: Cancer is a major global health concern, causing millions of deaths each year due to the uncontrolled growth and spread of abnormal cell...
Cancer is an evolutionary process characterized by profound intratumor heterogeneity (ITH), which can be quantified using in silico estimates of cance...
Publicly available, large-scale medical imaging datasets are crucial for developing and validating artificial intelligence (AI) models and conducting ...
Metabolic rewiring, a defining hallmark of cancer, sustains cell proliferation and biosynthesis while coordinating adaptive interactions within the tu...