colon-cancer
There are 0 repository under colon-cancer topic.
ramhiser / datamicroarray
A collection of small-sample, high-dimensional microarray data sets to assess machine-learning algorithms and models.
Language:R 101shiv213 / Artificial-Intelligence-for-Colon-Cancer-Detection
Image classifier for colon cancer detection from colonoscopies.
Language:Python 15koushikkumarl / capsuleNetwork_cancerclassification
Image classification on lung and colon cancer histopathological images through Capsule Networks or CapsNets.
Language:Jupyter Notebook 11DebeshJha / 2020-MediaEval-Medico-polyp-segmentation
GitHub repository for Medico automatic polyp segmentation challenge
Language:Python 10QuIIL / KBSMC_colon_cancer_grading_dataset
KBSMC colon cancer grading dataset repository
Language:Python 7Kvasir-SEG: A Segmented Polyp Dataset
nischaybikramthapa / colon-cancer-detection
Detection of Colon Cancer Cell and its types using a semi-supervised approach with deep learning
Language:Jupyter Notebook 5groupoasys / Medical_data
Repo which includes the medical data sets used in a feature selection paper proposed by OASYS group
alibrahimzada / Colon-Cancer
Exploring the Supervised Learning Models to Automatically Diagnose Colon Cancer Patients based on their SNP Profiles
Language:Jupyter Notebook 2roysouvik2 / colon_cancer_parameter_estimation_sensitivity_analysis
Codes for parameter estimation and sensitivity analysis of QSP models for colon cancer. This is a part of the National Cancer Institute funded project titled "Data-driven QSP software for personalized colon cancer treatment" Achyuth Manoj, Susanth Kakarla, Suvra Pal and Souvik Roy.
Language:MATLAB 2zimolzak / instruct-project-etrigger-sql
Find patients who have concerning tests but no timely follow-up
Language:TSQL 2gari3008ma / RNA-seq
colorectal cancer
matteodelucchi / CRC_TRs
TRAL pipeline for tandem repeat detection in proteins. Specifically in such which are related to colorectal cancer.
Language:Python 1KBSMC_colon_tma_cancer_grading_1024_dataset
Language:Python 1aastha1840 / ColonCancerMolecularSubtypeClassification
Colorectal cancer (CRC) is the second most dangerous type of cancer in terms of causing deaths in patients and third most common type of cancer found in people in terms of incidence. CRC can be further categorized based on its molecular subtypes. Each subtype displays different features. Thus, identifying molecular subtypes of CRC and treating patients accordingly can help achieve better therapeutic results rather than providing the same treatment for all colorectal cancer patients. Our research aims at identifying molecular subtypes of colorectal cancer using gene expression data by building a model using some machine learning and deep learning algorithms.
Language:Jupyter Notebook 0AI-Medical-Robotics / Colonoscopy-Lesion-Detection
Rasa Gastroenterologist AI Chatbot to help doctor detect patients colon cancer lesions using Unity, Darknet Yolo, Keras CNN
Language:Jupyter Notebook 0HuzeyfeAyaz / CRC_Prediction_with_Immune_SNP_Profiles
The goal of this analysis is to explore the machine learning-based automatic diagnosis of colorectal patients based on the single nucleotide polymorphisms (SNP). Such a computational approach may be used complementary to other diagnosis tools, such as, biopsy, CT scan, and MRI. Moreover, it may be used as a low-cost screening for colorectal cancers
Language:Jupyter Notebook 0Shivangi1Raghav / Colon-Cancer-Prediction
Colorectal cancer (CRC) is the second most dangerous type of cancer in terms of causing deaths in patients and third most common type of cancer found in people in terms of incidence. CRC can be further categorized based on its molecular subtypes. Each subtype displays different features. Thus, identifying molecular subtypes of CRC and treating patients accordingly can help achieve better therapeutic results rather than providing the same treatment for all colorectal cancer patients. Our research aims at identifying molecular subtypes of colorectal cancer using gene expression data by building a model using some machine learning and deep learning algorithms.
Language:Jupyter Notebook 0amatov / FragmentomicsSubclinicalDisease
breast-cancergastric-cancerlung-cancerovarian-cancerpancreatic-cancerbile-duct-cancerduodenal-cancercolon-adenomacolon-cancerdeep-learningrectal-adenomarectal-cancerearly-detectionsub-clinical-diseasefragmentation-patternsfragmentomicsdna-fragment-lengthwhole-genome-sequencingidentify-disease-stageearly-detection-of-diseaseLanguage:R- colon-cancerrectal-cancercolon-adenomadetect-recurrencepredict-relapserectal-adenomascikit-learnultra-deep-sequencingtumor-agnostic-approachclinical-trialsblacklisting-filtererror-rateslasso-regressionlimit-of-detectionunique-molecular-identifiersmutation-scorefragmentomicsdna-fragmentation-patternsdetection-error-ratessensitivity-specificityLanguage:R