Latest AI and machine learning research in oncology/hematology for healthcare professionals.
BACKGROUND: The management of head and neck cancer relies on multidisciplinary expertise; however, access to tumor boards remains variable. Large language models (LLMs) may support guideline-based decision-making, although performance in complex oncologic scenarios is not well defined. METHODS: Fourteen synthetic cases based on real tumor board encounters were evaluated. Five blinded comparator ar...
Recent advancements in cancer immunotherapy have transformed clinical oncology, with monoclonal antibodies (mAbs), immune checkpoint inhibitors, adoptive cellular therapies, oncolytic viruses, cytokine based therapeutics and nanomedicine establishing themselves as core treatment platforms. Tumor heterogeneity driven by inter and intra tumoral genomic divergence generates complex neoantigen landsca...
Brain tumors (BT) are actually an uncontrolled growth of cancer cells inside the body that can be classified into several classes according to their c...
Hepatocellular carcinoma (HCC) represents an extremely complex and heterogeneous malignant tumor. Protein palmitoylation, a highly conserved and pivot...
BACKGROUND: Evidence indicates that artificial intelligence (AI) can improve mammography screening by increasing cancer detection and reducing screen ...
BACKGROUND: Accurate assessment of mortality, bleeding, and atherothrombotic risk in patients with cancer and acute coronary syndrome could inform nov...
R-loops are dynamic nucleic acid structures implicated in genome regulation and instability, yet their contributions to the tumor microenvironment (TM...
The integration of artificial intelligence, protein engineering, and sustainable nanomedicine is driving a paradigm shift in theranostics by enabling ...
The digital twin (DT) concept, originating from engineering disciplines, has emerged as a transformative technology in healthcare, particularly in onc...
BACKGROUND: In HR+/HER2- metastatic breast cancer (MBC), CDK4/6 inhibitors combined with endocrine therapy (ET) significantly improve progression-free...
Resistance to lenvatinib has become a major obstacle in the clinical treatment of liver cancer, highlighting the significant research value and transl...
Clinical trial enrollment in oncology remains limited by increasingly complex eligibility criteria, biomarker stratification, and fragmented clinical ...
Neoadjuvant therapy is a cornerstone of modern oncology, yet its efficacy is traditionally assessed only after treatment completion, creating a "black...
OBJECTIVES: Prostate cancer (PCa) diagnosis is increasingly guided by imaging, with ultrasound (US) emerging as a cost-effective and widely accessible...
Studying how actin filaments are assembled into different subcellular structures can provide insights into both physiological processes and the mechan...
BACKGROUND: Artificial intelligence, particularly machine learning, has great potential to improve health outcomes, including predicting adverse condi...
Ribonucleic acid (RNA) modifications, once viewed as static structural features, are now recognized as dynamic regulators of the 'epitranscriptome' th...
BACKGROUND: Existing pancreatic cancer prediction models still have significant limitations until now. This multicenter retrospective study aimed to i...
PURPOSE: Radiation-free tools, such as scoliometers, ultrasound, and Moiré topography, have been explored for monitoring Adolescent Idiopathic Scolios...