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Colorectal Neoplasms

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Machine learning phenomics (MLP) combining deep learning with time-lapse-microscopy for monitoring colorectal adenocarcinoma cells gene expression and drug-response.

Scientific reports
High-throughput phenotyping is becoming increasingly available thanks to analytical and bioinformatics approaches that enable the use of very high-dimensional data and to the availability of dynamic models that link phenomena across levels: from gene...

Special issue "The advance of solid tumor research in China": Prognosis prediction for stage II colorectal cancer by fusing computed tomography radiomics and deep-learning features of primary lesions and peripheral lymph nodes.

International journal of cancer
Currently, the prognosis assessment of stage II colorectal cancer (CRC) remains a difficult clinical problem; therefore, more accurate prognostic predictors must be developed. In our study, we developed a prognostic prediction model for stage II CRC ...

Short-term results of robot-assisted colorectal cancer surgery using Senhance Digital Laparoscopy System.

Asian journal of endoscopic surgery
BACKGROUND: The Senhance Digital Laparoscopy System (Asensus Surgical Inc, Morrisville, NC, United States), which was introduced for the first time in Japan by our hospital, is a new surgical assistive robot following the da Vinci Surgical System. We...

Spatial analysis of tumor-infiltrating lymphocytes in histological sections using deep learning techniques predicts survival in colorectal carcinoma.

The journal of pathology. Clinical research
This study aimed to explore the prognostic impact of spatial distribution of tumor-infiltrating lymphocytes (TILs) quantified by deep learning (DL) approaches based on digitalized whole-slide images stained with hematoxylin and eosin in patients with...

Detection and Classification of Colorectal Polyp Using Deep Learning.

BioMed research international
Colorectal Cancer (CRC) is the third most dangerous cancer in the world and also increasing day by day. So, timely and accurate diagnosis is required to save the life of patients. Cancer grows from polyps which can be either cancerous or noncancerous...

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI) tools increase detection of precancerous polyps during colonoscopy and might contribute to long-term colorectal cancer prevention. The aim of the study was to investigate the incremental effect of the implemen...

COVID-CCD-Net: COVID-19 and colon cancer diagnosis system with optimized CNN hyperparameters using gradient-based optimizer.

Medical & biological engineering & computing
Coronavirus disease-2019 (COVID-19) is a new types of coronavirus which have turned into a pandemic within a short time. Reverse transcription-polymerase chain reaction (RT-PCR) test is used for the diagnosis of COVID-19 in national healthcare center...

Bioinformatics analysis reveals immune prognostic markers for overall survival of colorectal cancer patients: a novel machine learning survival predictive system.

BMC bioinformatics
OBJECTIVES: Immune microenvironment was closely related to the occurrence and progression of colorectal cancer (CRC). The objective of the current research was to develop and verify a Machine learning survival predictive system for CRC based on immun...

Robot-Assisted Right Colectomy with Sequential Wedge Resection of Segments 4 and 5 of The Liver and Cholecystectomy for Colon Cancer with Metastasis to The Liver.

The American surgeon
The liver is the most common place for colon adenocarcinoma metastasis because of portal circulation. The surgical intervention for patients with colon adenocarcinoma with synchronous metastasis to the liver has been debated. Studies have shown that ...