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Colonic Neoplasms

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A data-driven approach to a chemotherapy recommendation model based on deep learning for patients with colorectal cancer in Korea.

BMC medical informatics and decision making
BACKGROUND: Clinical Decision Support Systems (CDSSs) have recently attracted attention as a method for minimizing medical errors. Existing CDSSs are limited in that they do not reflect actual data. To overcome this limitation, we propose a CDSS base...

Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice.

BMC medical genomics
BACKGROUND: Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. Molecular level characters, such as gene expression levels and mutations, may provide profound information for precision treatment apart from path...

A comprehensive review of deep learning in colon cancer.

Computers in biology and medicine
Deep learning has emerged as a leading machine learning tool in object detection and has attracted attention with its achievements in progressing medical image analysis. Convolutional Neural Networks (CNNs) are the most preferred method of deep learn...

Preliminary exploration of robotic complete mesocolic excision for colon cancer with the domestically produced Chinese minimally invasive Micro Hand S surgical robot system.

The international journal of medical robotics + computer assisted surgery : MRCAS
OBJECTIVE: To summarize our initial experience with robot-assisted complete mesocolic excision (R-CME) using a domestically produced Chinese surgical robot by a short-term evaluation.

Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage.

PloS one
BACKGROUND: Cancer is the second leading cause of death in the United States. Cancer screenings can detect precancerous cells and allow for earlier diagnosis and treatment. Our purpose was to better understand risk factors for cancer screenings and a...

Molecular docking and machine learning analysis of Abemaciclib in colon cancer.

BMC molecular and cell biology
BACKGROUND: The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is personalised opens the doors to the design ...

A machine learning-based prognostic predictor for stage III colon cancer.

Scientific reports
Limited biomarkers have been identified as prognostic predictors for stage III colon cancer. To combat this shortfall, we developed a computer-aided approach which combing convolutional neural network with machine classifier to predict the prognosis ...

Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study.

Gastroenterology
BACKGROUND AND AIMS: Up to 30% of adenomas might be missed during screening colonoscopy-these could be polyps that appear on-screen but are not recognized by endoscopists or polyps that are in locations that do not appear on the screen at all. Comput...

A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems.

mBio
Machine learning (ML) modeling of the human microbiome has the potential to identify microbial biomarkers and aid in the diagnosis of many diseases such as inflammatory bowel disease, diabetes, and colorectal cancer. Progress has been made toward dev...