Latest AI and machine learning research in colon cancer for healthcare professionals.
The differentiation between pathological subtypes of non-small cell lung cancer (NSCLC) is an essential step in guiding treatment options and prognosis. However, current clinical practice relies on multi-step staining and labelling processes that are time-intensive and costly, requiring highly specialised expertise. In this study, we propose a label-free methodology that facilitates autofluorescen...
BACKGROUND AND OBJECTIVE: Crohn's disease (CD) and colorectal cancer (CRC) share many clinical symptoms, making non-invasive differential diagnosis difficult. FIT-sDNA is sensitive for CRC screening in average-risk populations but often gives false positives in CD patients due to inflammation-induced mucosal turnover. This study aimed to develop and validate an algorithm-enhanced system (FIT-sDNA-...
BACKGROUND: Compared with conventional colonoscopy, computer-assisted adenoma detection (CADe) colonoscopy and Endocuff-Vision (EV) have been shown to...
BACKGROUND: Predicting response to immune checkpoint inhibitor plus tyrosine kinase inhibitor (IO+TKI) therapy in metastatic renal cell carcinoma (mRC...
UNLABELLED: Metastasis is the leading cause of cancer deaths. To develop strategies for intercepting metastatic progression, a better understanding of...
Immunotherapy has revolutionized cancer treatment, yet characterizing the spatial complexity of the tumor immune microenvironment remains a challenge....
Pathology report generation has received increasing attention in recent years. However, existing pathology report generation methods still face two ma...
BACKGROUND: A high adenoma detection rate in screening colonoscopy is associated with decreased rates of post-colonoscopy colorectal cancer. The use o...
Computer-aided colonoscopy (CAC) may improve polyp detection and characterization compared to traditional colonoscopy (TC). However, recent studies al...
BACKGROUND: In clinical stage IA lung adenocarcinoma (LUAD), rapid and accurate intraoperative diagnosis is crucial to decide whether to perform segme...
BACKGROUND: Robotic colorectal surgery has achieved widespread clinical adoption, yet meaningful standardisation of intraoperative practice remains li...
BACKGROUND AND AIMS: Computer-aided detection (CADe) is anticipated to enhance adenoma detection rate (ADRs). The aim of this study was to systematica...
OBJECTIVES: The precise prediction by MSI plays a key role in the perioperative treatment and prognosis of colorectal cancer (CRC) patients. This stud...
Pediatric neuro-oncology is a critical field of neurosurgery, representing the leading cause of disease-related mortality in children. Despite its rar...
The purpose of this study was to investigate the efficacy of a three-dimensional (3D) deep learning (DL) model in predicting recurrence risk of stage ...
PURPOSE: Lung adenocarcinoma (LUAD), the most common subtype of non-small cell lung cancer (NSCLC), often presents with mild or absent symptoms in its...
MOTIVATION: Single-cell RNA sequencing (scRNA-seq) data analysis is often performed using network projections that produce co-expression networks. The...
BACKGROUND: Artificial intelligence (AI) is rapidly transforming colorectal surgery through applications spanning screening to postoperative care. Thi...
With the advancement of deep learning, polyp segmentation in endoscopic images has achieved remarkable progress. However, clinical polyps often exhibi...