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Colorectal Neoplasms

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ChatGPT as a patient education tool in colorectal cancer-An in-depth assessment of efficacy, quality and readability.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland
AIM: Artificial intelligence (AI) chatbots such as Chat Generative Pretrained Transformer-4 (ChatGPT-4) have made significant strides in generating human-like responses. Trained on an extensive corpus of medical literature, ChatGPT-4 has the potentia...

Deep learning for segmentation of colorectal carcinomas on endoscopic ultrasound.

Techniques in coloproctology
BACKGROUND: Bowel-preserving local resection of early rectal cancer is less successful if the tumor infiltrates the muscularis propria as opposed to submucosal infiltration only. Magnetic resonance imaging currently lacks the spatial resolution to pr...

Development of a urine-based metabolomics approach for multi-cancer screening and tumor origin prediction.

Frontiers in immunology
BACKGROUND: Cancer remains a leading cause of mortality worldwide. A non-invasive screening solution was required for early diagnosis of cancer. Multi-cancer early detection (MCED) tests have been considered to address the challenge by simultaneously...

CE-Net: Cascade attention and context-aware cross-level fusion network via edge learning guidance for polyp segmentation.

Computers in biology and medicine
Colorectal polyps are one of the most direct causes of colorectal cancer. Polypectomy can effectively block the process of colorectal cancer, but accurate polyp segmentation methods are required as an auxiliary means. However, there are several chall...

Object-based feedback attention in convolutional neural networks improves tumour detection in digital pathology.

Scientific reports
Human visual attention allows prior knowledge or expectations to influence visual processing, allocating limited computational resources to only that part of the image that are likely to behaviourally important. Here, we present an image recognition ...

Early colorectal cancer detection: a serum analysis platform combining SERS and machine learning.

Analytical methods : advancing methods and applications
Colorectal cancer (CRC) is one of the deadliest malignancies globally, with high incidence and mortality rates. Early detection is crucial for improving treatment success rates and patient survival. However, due to the difficulty in detecting early s...

Exploring vision transformers and XGBoost as deep learning ensembles for transforming carcinoma recognition.

Scientific reports
Early detection of colorectal carcinoma (CRC), one of the most prevalent forms of cancer worldwide, significantly enhances the prognosis of patients. This research presents a new method for improving CRC detection using a deep learning ensemble with ...

Deep learning-assisted colonoscopy images for prediction of mismatch repair deficiency in colorectal cancer.

Surgical endoscopy
BACKGROUND: Deficient mismatch repair or microsatellite instability is a major predictive biomarker for the efficacy of immune checkpoint inhibitors of colorectal cancer. However, routine testing has not been uniformly implemented due to cost and res...

Accurate prediction of colorectal cancer diagnosis using machine learning based on immunohistochemistry pathological images.

Scientific reports
Colorectal cancer (CRC) ranks as the third most prevalent tumor and the second leading cause of mortality. Early and accurate diagnosis holds significant importance in enhancing patient treatment and prognosis. Machine learning technology and bioinfo...