Colon Cancer

Effect of Static vs. Conversational AI-Generated Messages on Colorectal Cancer Screening Intent: a Randomized Controlled Trial

Large language model (LLM) chatbots show increasing promise in persuasive communication. Yet their real-world utility remains uncertain, particularly in clinical settings where sustained conversations are difficult to scale. In a pre-registered randomized controlled trial, we enrolled 915 U.S. adults (ages 45-75) who had never completed colorectal cancer (CRC) screening. Participants were random...

Mid-level data fusion of pleural effusion SERS spectra and serum CEA levels using machine learning algorithms for precise lung cancer detection.

Accurate identification of clinically malignant pleural effusions is critical for cancer diagnosis and subsequent treatment planning. Here, surface-enhanced Raman spectroscopy (SERS) data of pleural effusions and serum carcinoembryonic antigen (CEA) levels were integrated to develop an innovative mid-level data fusion method combined with machine learning algorithms to improve the accuracy of canc...

CL-Polyp: A Contrastive Learning-Enhanced Network for Accurate Polyp Segmentation

Accurate segmentation of polyps from colonoscopy images is crucial for the early diagnosis and treatment of colorectal cancer. Most existing deep le...

ADPv2: A Hierarchical Histological Tissue Type-Annotated Dataset for Potential Biomarker Discovery of Colorectal Disease

Computational pathology (CoPath) leverages histopathology images to enhance diagnostic precision and reproducibility in clinical pathology. However,...

Serum-Based Detection of Pancreatic and Ovarian Cancer via a Nanoparticle-Enhanced Fluorescence Array and Machine Learning.

: Early detection of oncological diseases such as pancreatic ductal adenocarcinoma (PDAC) and ovarian cancer (OV) is pivotal for successful treatment ...

Label-free single-cell phenotyping to determine tumor cell heterogeneity in pancreatic cancer in real time.

Resistance to chemotherapy of pancreatic ductal adenocarcinoma (PDAC) is largely driven by intratumoral heterogeneity (ITH) due to tumor cell plastici...

HGNet: High-Order Spatial Awareness Hypergraph and Multi-Scale Context Attention Network for Colorectal Polyp Detection

Colorectal cancer (CRC) is closely linked to the malignant transformation of colorectal polyps, making early detection essential. However, current m...

Colorectal Cancer Tumor Grade Segmentation in Digital Histopathology Images: From Giga to Mini Challenge

Colorectal cancer (CRC) is the third most diagnosed cancer and the second leading cause of cancer-related death worldwide. Accurate histopathologica...

Protocol for a multicenter randomized controlled trial to assess the usefulness of computer-aided detection systems for colonoscopy in colorectal cancer screening in the Asia-Pacific region (project CAD/NCCH2217).

Ensuring the high quality of colonoscopies in colorectal cancer (CRC) screening is essential to reducing CRC. Recently, computer-aided detection syste...

Rapid diagnosis of lung cancer by multi-modal spectral data combined with deep learning.

Lung cancer is a malignant tumor that poses a serious threat to human health. Existing lung cancer diagnostic techniques face the challenges of high c...

MEGANet-W: A Wavelet-Driven Edge-Guided Attention Framework for Weak Boundary Polyp Detection

Colorectal polyp segmentation is critical for early detection of colorectal cancer, yet weak and low contrast boundaries significantly limit automat...

Temporally-Aware Supervised Contrastive Learning for Polyp Counting in Colonoscopy

Automated polyp counting in colonoscopy is a crucial step toward automated procedure reporting and quality control, aiming to enhance the cost-effec...

Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation

Polyp segmentation in colonoscopy images is crucial for early detection and diagnosis of colorectal cancer. However, this task remains a significant...

Cells Keep Diverse Company in Diseased Tissues.

Emerging spatial profiling technologies have revolutionized our understanding of how tissue architecture shapes disease progression, yet the contribut...

Accurate Diagnosis of Colorectal Cancer Using a Combination of Lectin-Induced Recombinase Polymerase Amplification and CRISPR/Cas12a Assay on a Point-of-Care Testing Platform with Deep Learning Assistant.

Specific glycosylation patterns on exosome surfaces represent novel diagnostic biomarkers for cancer liquid biopsy. Lectins can induce exosome aggrega...

Medical management of pancreatic cancer: from personalization to broadening treatment strategies.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most heterogeneous and deadly cancers. This review examines recently implemented strategies to i...

Computer-aided unveiling molecular mechanisms of Xylocarpus granatum against colorectal cancer: therapeutic intervention targeting P13K-AKT signaling pathway.

Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality globally, with increasing incidence rates, particularly in early-...

Integrating AI/ML and multi-omics approaches to investigate the role of TNFRSF10A/TRAILR1 and its potential targets in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival of under 10 % despite current therapies...

Multimodal AI framework for lung cancer diagnosis: Integrating CNN and ANN models for imaging and clinical data analysis.

Lung cancer remains a leading cause of cancer-related mortality worldwide, emphasizing the critical need for accurate and early diagnostic solutions. ...

From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction.

Pancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, characterized by late-stage diagnosis and limited therap...