Latest AI and machine learning research in oncology/hematology for healthcare professionals.
BACKGROUND: Artificial intelligence (AI) is being rapidly integrated into oncologic care, yet little is known about how patients perceive these applications. Understanding patient perceptions is critical to ensuring AI applications align with their needs and preferences. OBJECTIVE: This study aimed to evaluate oncology patients' attitudes and beliefs on the use of AI across clinical touchpoints in...
This review examines how biotechnology advances (CRISPR/Cas9, next-generation targeted therapies, nanotechnology-based drug delivery, and immunotherapies) can be applied to address cancer drug resistance worldwide. It also considers the economic burden of resistance, inequities in access to biotechnology solutions, and ethical concerns surrounding rapid innovation, particularly in low-resource set...
Esophageal squamous cell carcinoma (ESCC) remains a major health burden, particularly in Asia, with poor patient prognosis despite advancements in rad...
Hepatocellular carcinoma (HCC), the predominant form of primary liver cancer, ranks as the fourth leading cause of cancer-associated mortality globall...
Pulmonary embolism (PE) is a life-threatening condition for which computed tomography pulmonary angiography (CTPA) is the standard diagnostic modality...
Multidisciplinary teams (MDTs) are central to treatment planning for colorectal cancer liver metastases (CRCLM) but require time and consistent access...
Carotid CT angiography (CTA) is valuable for diagnosing carotid artery disease but involves radiation and contrast agent risks. Deep Learning Image Re...
Deep learning is expected to aid pathologists in tasks such as tumour segmentation. We developed a general tumour segmentation model for histopatholog...
BACKGROUND AND OBJECTIVE: Peripheral artery disease (PAD) is an atherosclerotic disorder prevalent in the elderly that leads to peripheral function de...
For the discovery and optimization of personalized cancer treatments using immune cell therapeutics, such as T-cell receptor (TCR-T) therapy and bispe...
PURPOSE: To leverage artificial intelligence-based OCT analysis to classify age-related macular degeneration (AMD) images into distinct subgroups base...
BACKGROUND: This study aimed to explore the functions and potential mechanisms of PIWI-interacting RNA-related genes (piRPGs) in bladder cancer (BC) d...
BACKGROUND: Multiplex immunofluorescence imaging enables detailed characterization of the tumor immune microenvironment, but whether immune cell densi...
AIMS: In percutaneous coronary intervention (PCI), a suboptimal choice of guiding catheter may compromise coaxial alignment and backup support, prolon...
Oral squamous cell carcinoma (OSCC), the most common oral malignancy, requires accurate diagnostic methods for patient stratification and treatment gu...
Tumor Mutational Burden (TMB) is a widely used biomarker for selecting cancer patients for immune checkpoint inhibitor (ICI) therapy. However, TMB alo...
BACKGROUND: Metabolomics is a valuable tool for characterising biological mechanisms involved in cancer development, but produces complex datasets wit...
Multiplex live imaging enables simultaneous visualization of multiple signaling pathways in living cells, offering real-time insights into complex cel...
PURPOSE: Artificial Intelligence (AI) and Machine Learning (ML) are being explored to improve systematic evidence gathering and to identify patterns a...
BACKGROUND: Preoperative differentiation of precursor glandular lesions (PGL), minimally invasive (MIA), and invasive adenocarcinoma (IAC) in stage IA...