Latest AI and machine learning research in colon cancer for healthcare professionals.
Cancers are caused by genomic alterations that may be inherited, induced by environmental carcinogens, or caused due to random replication errors. Postinduction of carcinogenicity, mutations further propagate and drastically alter the cancer genomes. Although a subset of driver mutations has been identified and characterized to date, most cancer-related somatic mutations are indistinguishable from...
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 such amalgamated (dual-domain) data sets. The aim of the associated algorithms is to identify geographically efficient clusters that also maximize the...
BACKGROUND: We aimed to develop a deep learning (DL) model to predict DNA mismatch repair (MMR) status in colorectal cancers (CRC) based on hematoxyli...
We present a protocol which implements deep learning-based identification of the lung adenocarcinoma category with high accuracy and generalizability,...
In a colonoscopy, accurate computer-aided polyp detection and segmentation can help endoscopists to remove abnormal tissue. This reduces the chance of...
OBJECTIVE: Application effect of Leonardo's robot-assisted laparoscopy in hepatectomy for colorectal cancer patients with liver metastases.
Colorectal cancer (CRC) is the third most common cancer worldwide. Although clinical outcome varies among patients diagnosed within the same TNM stage...
INTRODUCTION: Artificial intelligence has been rapidly deployed in gastroenterology and endoscopy. The acceleration of deep convolutional neural netwo...
The study aims to investigate perioperative indices and immediate outcomes of laparoscopic and robotic surgical interventions in colorectal cancer pat...
BACKGROUND : There are several types of pancreatic mass, so it is important to distinguish between them before treatment. Artificial intelligence (AI)...
Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotype...
Zhenqi Fuzheng formula (ZQFZ), of which the main ingredients are and , has immune system regulatory functions and potential anti-tumor bioactivity. T...
Analyzing the biological data by considering the molecule interactions may induce a more accurate identification of disease-related biomarkers. In thi...
Robotic-assisted colorectal surgery (RACS) is steadily increasing in popularity with an annual growth in the number of colorectal procedures undertake...
Colon cancer is a disease characterized by the unusual and uncontrolled development of cells that are found in the large intestine. If the tumour exte...
The potential role of tadalafil, a PDE5 inhibitor, in anticancer activity and prolonged survival has been proposed. However, the systematic effects of...
BACKGROUND AND OBJECTIVE: Adjuvant chemotherapy is recommended as standard treatment for colorectal cancer (CRC) with stage III according to TNM stage...
This study aimed to explore the value of abdominal computerized tomography (CT) three-dimensional reconstruction using the dense residual single-axis ...
Tissue-level semantic segmentation is a vital step in computational pathology. Fully-supervised models have already achieved outstanding performance w...
High-throughput phenotyping is becoming increasingly available thanks to analytical and bioinformatics approaches that enable the use of very high-dim...