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Colorectal Neoplasms

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HunCRC: annotated pathological slides to enhance deep learning applications in colorectal cancer screening.

Scientific data
Histopathology is the gold standard method for staging and grading human tumors and provides critical information for the oncoteam's decision making. Highly-trained pathologists are needed for careful microscopic analysis of the slides produced from ...

Unsupervised learning methods for efficient geographic clustering and identification of disease disparities with applications to county-level colorectal cancer incidence in California.

Health care management science
Many public health policymaking questions involve data subsets representing application-specific attributes and geographic location. We develop and evaluate standard and tailored techniques for clustering via unsupervised learning (UL) algorithms on ...

Clinical actionability of triaging DNA mismatch repair deficient colorectal cancer from biopsy samples using deep learning.

EBioMedicine
BACKGROUND: We aimed to develop a deep learning (DL) model to predict DNA mismatch repair (MMR) status in colorectal cancers (CRC) based on hematoxylin and eosin-stained whole-slide images (WSIs) and assess its clinical applicability.

Application Effect of Robot-Assisted Laparoscopy in Hepatectomy for Colorectal Cancer Patients with Liver Metastases.

Computational and mathematical methods in medicine
OBJECTIVE: Application effect of Leonardo's robot-assisted laparoscopy in hepatectomy for colorectal cancer patients with liver metastases.

Development of a Fully Automated Method to Obtain Reproducible Lymphocyte Counts in Patients With Colorectal Cancer.

Applied immunohistochemistry & molecular morphology : AIMM
Colorectal cancer (CRC) is the third most common cancer worldwide. Although clinical outcome varies among patients diagnosed within the same TNM stage it is the cornerstone in treatment decisions as well as follow-up programmes. Tumor-infiltrating ly...

Robotic and laparoscopic surgical procedures for colorectal cancer.

Journal of robotic surgery
The study aims to investigate perioperative indices and immediate outcomes of laparoscopic and robotic surgical interventions in colorectal cancer patients. The study included 163 patients [90 (55.2%) females and 73 (44.8%) males, aged 67.46 ± 6.72 y...

ZhenQi FuZheng formula inhibits the growth of colorectal tumors by modulating intestinal microflora-mediated immune function.

Aging
Zhenqi Fuzheng formula (ZQFZ), of which the main ingredients are and , has immune system regulatory functions and potential anti-tumor bioactivity. The inhibition of colorectal tumor growth by ZQFZ was analyzed in inflammatory cells and B6/JGpt-/Gpt...

A convolution neural network with multi-level convolutional and attention learning for classification of cancer grades and tissue structures in colon histopathological images.

Computers in biology and medicine
A clinically comparable Convolutional Neural Network framework-based technique for performing automated classification of cancer grades and tissue structures in hematoxylin and eosin-stained colon histopathological images is proposed in this paper. I...

Deep learning with whole slide images can improve the prognostic risk stratification with stage III colorectal cancer.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Adjuvant chemotherapy is recommended as standard treatment for colorectal cancer (CRC) with stage III according to TNM stage. However, outcomes are varied even among patients receiving similar treatments. We aimed to develop...

Diagnosis of Nonperitonealized Colorectal Cancer with Computerized Tomography Image Features under Deep Learning.

Contrast media & molecular imaging
This study aimed to explore the value of abdominal computerized tomography (CT) three-dimensional reconstruction using the dense residual single-axis super-resolution algorithm in the diagnosis of nonperitonealized colorectal cancer (CC). 103 patient...